Data processing method of digital twin system, storage medium and electronic equipment

Abstract

The invention discloses a data processing method of a digital twin system, a storage medium and electronic equipment. The method comprises the following steps: receiving a data processing instruction, and obtaining an original data source and a changed data source of the digital twin system; the digital twinborn objects in the changed data source are matched with the digital twinborn objects in the original data source to obtain a matching result, and the matching result is used for representing whether the digital twinborn objects in the changed data source and the digital twinborn objects in the original data source belong to the same digital twinborn entity or not; and changing the object attribute value of the digital twin object in the original data source based on the change type of the changed data source and the matching result to obtain a first change result. According to the method and the device, the technical problem of relatively low management efficiency of attribute change in a digital twin system in the related technology is solved.

Description

Technical Field

[0001] The present application relates to the field of digital twins, and more particularly, to a data processing method, a storage medium, and an electronic device for a digital twin system. Background Art

[0002] In a digital twin system, the management of the property version of an entity refers to the management process of changing and tracking the properties in the digital twin entity. In digital twins, a property refers to information describing the characteristics and states of an entity, which may include the position, shape, property value, etc. of the entity. The purpose of property version management is to record and track the historical changes of the properties of the digital twin entity, so as to trace and analyze the states and property values of the entity at different time points. Through property version management, the historical states of the entity can be visualized, analyzed, and compared, helping users understand the evolution process of the entity and the change trend of the property value, and providing support for decision-making and analysis.

[0003] The current property version management scheme of digital twin systems has many defects. For example, the changes in properties lead to inconsistent and incomplete data, resulting in poor ability of property version management in digital twin systems.

[0004] In response to the above problems, no effective solution has been proposed yet. Summary of the Invention

[0005] Embodiments of the present application provide a data processing method, a storage medium, and an electronic device for a digital twin system, so as to at least solve the technical problem of poor management efficiency of property changes in digital twin systems in related technologies.

[0006] According to one aspect of the embodiments of the present application, a data processing method for a digital twin system is provided. The digital twin system is used to manage a digital twin entity in the real world through a digital twin object in a virtual world. The method includes: receiving a data processing instruction, and obtaining an original data source and a change data source of the digital twin system; matching the digital twin object in the change data source with the digital twin object in the original data source to obtain a matching result, where the matching result is used to indicate whether the digital twin object in the change data source and the digital twin object in the original data source belong to the same digital twin entity; and changing the object property value of the digital twin object in the original data source based on the change type of the change data source and the matching result to obtain a first change result.

[0007] According to one aspect of the embodiments of the present application, a data processing method for a digital twin system is provided. The digital twin system is used to manage digital twin entities in the real world through digital twin objects in the virtual world. The method includes: responding to an operation instruction acting on an operation interface, and displaying the original data source and the changed data source of the digital twin system on the operation interface, where the digital twin system is used to associate digital twin objects in the virtual world with digital twin entities in the real world; responding to a processing instruction acting on the operation interface, and displaying a first change result on the operation interface, where the first change result is obtained by changing the object attribute values of the digital twin objects in the original data source based on the change type of the changed data source and the matching result, and the matching result is obtained by matching the digital twin objects in the changed data source with the digital twin objects in the original data source, where the matching result is used to indicate whether the digital twin objects in the changed data source and the digital twin objects in the original data source belong to the same digital twin entity.

[0008] According to one aspect of the embodiments of the present application, a data processing method for a digital twin system is provided. The digital twin system is used to manage digital twin entities in the real world through digital twin objects in the virtual world, and includes: responding to receiving a data processing instruction for the digital twin system, and obtaining the original data source and the changed data source of the digital twin system by calling a first interface, where the digital twin system is used to associate digital twin objects in the virtual world with digital twin entities in the real world, the first interface includes a first parameter, and the parameter value of the first parameter is the original data source and the changed data source; matching the digital twin objects in the changed data source with the digital twin objects in the original data source to obtain a matching result, where the matching result is used to indicate whether the digital twin objects in the changed data source and the digital twin objects in the original data source belong to the same digital twin entity; changing the object attribute values of the digital twin objects in the original data source based on the change type of the changed data source and the matching result to obtain a first change result; and outputting the first change result by calling a second interface, where the second interface includes a second parameter, and the parameter value of the second parameter is the first change result.

[0009] According to one aspect of the embodiments of the present application, a computer-readable storage medium is provided. The computer-readable storage medium includes an executable program stored therein. When the executable program runs, it controls the device where the computer-readable storage medium is located to execute the data processing method of the digital twin system in any one of the above embodiments.

[0010] According to one aspect of the embodiments of the present application, an electronic device is provided, including: a memory storing an executable program; and a processor for running the program, where when the program runs, it executes the data processing method of the digital twin system in any one of the above embodiments.

[0011] In an embodiment of the present application, first, a data processing instruction is received, and the original data source and the changed data source of the digital twin system are obtained; the digital twin objects in the changed data source are matched with the digital twin objects in the original data source to obtain a matching result, where the matching result is used to indicate whether the digital twin objects in the changed data source and the digital twin objects in the original data source belong to the same digital twin entity; based on the change type of the changed data source and the matching result, the object attribute values of the digital twin objects in the original data source are changed to obtain a first change result, which improves the management efficiency of attribute changes in the digital twin system. It is easy to note that the digital twin objects of different types in the received changed data source can be matched, so that the object attribute values of the digital twin objects in the original data source can be changed according to the object attribute values of the digital twin objects in the changed data source, so that the attribute changes of the digital twin objects are consistent, and the digital twin objects can display the same object attribute values among different users. By matching, the object attribute values corresponding to the digital twin objects can be updated, thereby improving the management efficiency of attribute changes, and further solving the technical problem of poor management efficiency of attribute changes in the digital twin system in the related art.

[0012] It is easy to note that the above general description and the following detailed description are only for exemplifying and explaining the present application, and do not constitute a limitation on the present application. Brief Description of the Drawings

[0013] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0014] Figure 1 is a hardware structure block diagram of a computer terminal (or mobile device) for implementing a data processing method of a digital twin system according to an embodiment of the present application;

[0015] Figure 2 is a flowchart of a data processing method of a digital twin system according to Embodiment 1 of the present application;

[0016] Figure 3 is a schematic diagram of digital twin object matching according to an embodiment of the present application;

[0017] Figure 4 is a schematic diagram of a data processing mechanism for slowly changing attributes according to an embodiment of the present application;

[0018] Figure 5 is a schematic diagram of a data processing mechanism for rapidly changing attributes according to an embodiment of the present application;

[0019] Figure 6 It is a schematic diagram of a digital twin object management page according to an embodiment of the present application;

[0020] Figure 7 It is a schematic diagram of a recovery and rollback mechanism according to an embodiment of the present application;

[0021] Figure 8 It is a schematic diagram of an attribute change prediction model according to an embodiment of the present application;

[0022] Figure 9 It is a flowchart of a data processing method of a digital twin system according to Embodiment 2 of the present application;

[0023] Figure 10 It is a flowchart of a data processing method of a digital twin system according to Embodiment 3 of the present application;

[0024] Figure 11 It is a schematic diagram of a data processing device of a digital twin system according to an embodiment of the present application;

[0025] Figure 12 It is a schematic diagram of a data processing device of a digital twin system according to an embodiment of the present application;

[0026] Figure 13 It is a schematic diagram of a data processing device of a digital twin system according to an embodiment of the present application;

[0027] Figure 14 It is a block diagram of the structure of a computer terminal according to an embodiment of the present application. Detailed implementation manners

[0028] In order to enable those skilled in the art to better understand the solution of the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present application.

[0029] It should be noted that the terms "first", "second", etc. in the description, claims, and the above-mentioned drawings of this application are used to distinguish similar objects, and do not necessarily have to be used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged under appropriate circumstances, so that the embodiments of this application described here can be implemented in an order other than those illustrated or described here. In addition, the terms "comprising" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or device that includes a series of steps or units does not necessarily have to be limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or are inherent to these processes, methods, products, or devices.

[0030] First, some of the nouns or terms that appear in the process of describing the embodiments of this application are applicable to the following explanations:

[0031] A digital twin entity refers to a virtual entity that models, simulates, and monitors entities or systems in the real world through digital technology, and is a symbol of a certain type of object. The entity in this application refers to a digital twin entity;

[0032] A digital twin object refers to the specific implementation of a digital twin entity, such as the virtual expression of a specific camera in the real world, the virtual expression of a traffic signal, etc.;

[0033] A digital twin system refers to a comprehensive system built based on digital twin technology. By integrating and connecting entities or systems in the real world with their digital twin entities, it realizes the monitoring, simulation, analysis, and update of the entities;

[0034] Slow change means that the attribute value remains relatively stable for a long time. In this case, the change of the attribute value is gradual, changing with a small amplitude and frequency. For example, attributes such as a person's age, gender, and date of birth are usually slowly changing, so they usually remain relatively stable for a long time;

[0035] Fast change means that the attribute value changes frequently in a short time. In this case, the change of the attribute value is sudden and large. For example, attributes such as stock prices and weather conditions are usually fast-changing because they can change multiple times in a short time;

[0036] Static attribute, among the attributes of a digital twin entity, an attribute that changes slowly is called a static attribute;

[0037] Dynamic attribute, among the attributes of a digital twin entity, an attribute that changes quickly is called a dynamic attribute;

[0038] A time window refers to a mechanism for grouping and processing data streams within a certain time range in real-time data processing;

[0039] A timing diagram refers to a planar graph with the moment value as the X-axis and the digital twin entity attribute value as the Y-axis;

[0040] A periodic snapshot fact table samples the metrics of an entity at determined intervals to facilitate the study of the entity's metric values, without the need to aggregate long-term transaction histories;

[0041] An accumulated snapshot fact table is used to track the progress of a series of tasks of an entity and usually has multiple date fields for studying the time intervals of milestones in the task process;

[0042] Identity mapping / Id Mapping is an algorithm used between different operating systems or data sources to match and unify different expressions of the same digital twin object;

[0043] An attribute change record is used to record the detailed information of attribute changes, including the time of change, the name of the changed attribute, the old value, and the new value, etc.;

[0044] Version tracing can trace the historical status and attribute values of entity attributes according to time or specific version numbers;

[0045] Attribute comparison can compare the attribute differences between different versions to analyze and understand the reasons and trends of attribute changes;

[0046] Attribute rollback can restore to the attribute state of a previous version to restore the entity to its previous attribute configuration;

[0047] Permission management can define different permissions and access levels for different users or roles to ensure the security and controllability of attribute version management.

[0048] The current method of attribute version management in digital twin systems stems from the following three defects:

[0049] (1) Lack of records of attribute changes, making it difficult to trace and roll back. Most digital twin systems display the current attributes of entities, but there is no standard record of various attribute changes and reasons, making it difficult to support historical tracing and auditing, and also difficult to roll back attributes when there are data problems;

[0050] (2) Attribute changes lead to data inconsistency and incompleteness. After attribute changes, due to the time difference between different systems or different users, the same attribute of the same object may show different attribute values for different users, resulting in data inconsistency;

[0051] (3) It is difficult to support time series analysis. Due to the lack of changes in attribute values, it is difficult to analyze and predict the change rules of attributes based on the time sequence, resulting in a decline in the user's ability to understand attribute changes.

[0052] This application provides a set of general data processing mechanisms. It can record the changes of slow static attributes for different types of digital twin entities or specific twin objects, and conveniently support subsequent query of change details and simulation deduction operations. It can record the changes of fast-changing dynamic attributes for different types of digital twin entities and specific twin objects, and conveniently support subsequent query of change details and simulation deduction operations. It provides a set of general recovery and rollback mechanisms. When errors or accidents occur, it supports operators to restore the historical version attributes of digital twin objects. It provides a set of general attribute change prediction models, which provide predicted attribute values for a specified future time period based on the historical change characteristics of attributes.

[0053] Embodiment 1

[0054] According to an embodiment of the present application, an embodiment of a data processing method for a digital twin system is also provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions. And although the logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in a different order than here.

[0055] The method embodiment provided by the first embodiment of the present application can be executed on a mobile terminal, a computer terminal or a similar computing device. Figure 1 It is a hardware structure block diagram of a computer terminal (or mobile device) for implementing the data processing method of the digital twin system according to an embodiment of the present application. As Figure 1 shown, the computer terminal 10 (or mobile device) may include one or more processors 102 (shown as 102a, 102b,..., 102n in the figure). The processor 102 may include, but is not limited to, a processing device such as a microcontroller unit (MCU) or a field-programmable gate array (FPGA). A memory 104 for storing data, and a transmission device 106 for communication functions. In addition, it may further include: a display, an input / output interface (I / O interface), a universal serial bus (USB) port, a network interface, a power supply, and / or a camera. Those of ordinary skill in the art can understand, Figure 1The structure shown is only schematic and does not limit the structure of the above-mentioned electronic device. For example, the computer terminal 10 may further include more or fewer components than those shown in Figure 1 or have a different configuration from that shown in Figure 1 .

[0056] It should be noted that the above one or more processors 102 and / or other data processing circuits can generally be referred to as "data processing circuits" herein. The data processing circuit can be embodied in software, hardware, firmware or any combination thereof, in whole or in part. In addition, the data processing circuit can be a single independent processing module, or be incorporated in whole or in part into any one of other elements in the computer terminal 10 (or mobile device). As involved in the embodiments of the present application, the data processing circuit is a kind of processor control (such as the selection of a variable resistance terminal path connected to an interface).

[0057] The memory 104 can be used to store software programs and modules of application software, such as the program instructions / data storage devices corresponding to the data processing method of the digital twin system in the embodiments of the present application. The processor 102 executes various functional applications and data processing by running the software programs and modules stored in the memory 104, that is, realizes the data processing method of the above digital twin system. The memory 104 may include a high-speed random access memory, and may also include a non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memories. In some instances, the memory 104 may further include a memory remotely disposed relative to the processor 102, and these remote memories can be connected to the computer terminal 10 through a network. Examples of the above network include but are not limited to the Internet, enterprise intranet, local area network, mobile communication network and combinations thereof.

[0058] The transmission device 106 is used to receive or send data via a network. Specific examples of the above network may include the wireless network provided by the communication provider of the computer terminal 10. In one instance, the transmission device 106 includes a network adapter (Network Interface Controller, NIC), which can be connected to other network devices through a base station and thus can communicate with the Internet. In one instance, the transmission device 106 can be a radio frequency (RF) module, which is used to communicate with the Internet wirelessly.

[0059] The display can be, for example, a touch-screen liquid crystal display (Liquid Crystal Display, abbreviated as LCD), and the liquid crystal display enables a user to interact with the user interface of the computer terminal 10 (or mobile device).

[0060] It should be noted that, in some alternative embodiments, the above Figure 1 shown computer device (or mobile device) may include hardware elements (including circuits), software elements (including computer code stored on a computer-readable medium), or a combination of both hardware elements and software elements. It should be pointed out that Figure 1 is only an example of a specific concrete instance and is intended to illustrate the types of components that may exist in the above computer device (or mobile device).

[0061] Under the above operating environment, the present application provides a data processing method for the digital twin system as shown in Figure 2 shown. Figure 2 is a flowchart of a data processing method for a digital twin system according to Embodiment 1 of the present application. As shown in Figure 2 shown, the server 10 can be connected to one or more client devices 20 through a local area network connection, a wide area network connection, an Internet connection, or other types of data networks. Here, the client devices 20 may include, but are not limited to: smart phones, tablets, laptops, handheld computers, personal computers, smart home devices, vehicle-mounted devices, etc. The client device 20 can interact with the user through a graphical user interface. The method includes:

[0062] Step S202, receiving a data processing instruction, and obtaining the original data source and the changed data source of the digital twin system.

[0063] Among them, the digital twin system is used to associate digital twin objects in the virtual world with digital twin entities in the real world.

[0064] The above data processing instruction may be an instruction generated after the digital twin system receives the changed data source.

[0065] The above original data source may be the data source obtained after the last processing of the digital twin system, and the above original data source may also be the most original data source when the digital twin system has not been processed. Here, the original data source is not specifically limited, and the original data source can be determined according to the actual situation.

[0066] The above changed data source contains different change attributes. For example, slow change attributes and fast change attributes are only used as examples here. The slow change attribute refers to the situation where the attribute value of the data in the changed data source remains relatively stable for a long time, and the fast change attribute refers to the situation where the attribute value of the data in the changed data source changes frequently in a short time.

[0067] For the changed data source with slow change attributes, it may come from external data source non-real-time data, algorithm batch-generated objects, page manual revision objects, and event information associated with digital twin objects, but is not limited thereto.

[0068] For the data source of changes to rapidly changing attributes, it can come from real-time data of external data sources, sensor data, Internet of Things data (abbreviated as IoT), but not limited to this.

[0069] The above-mentioned digital twin entity refers to a virtual entity that models, simulates, and monitors entities or systems in the real world through digital technology, and is a symbol of a certain type of object.

[0070] The above-mentioned digital twin object refers to the specific implementation of the digital twin entity in the virtual world. For example, the virtual expression of a specific camera in the real world in the virtual world, the virtual expression of a traffic signal light in the real world in the virtual world, etc.

[0071] The above-mentioned digital twin system refers to a comprehensive system constructed by digital twin technology. By integrating and connecting entities or systems in the real world with digital twin entities, entity monitoring, simulation, analysis, and update are realized.

[0072] In an alternative embodiment, when a data processing instruction is received, the existing original data source and the newly received change data source of the digital twin system can be obtained, so as to change the original data source of the digital twin system according to the data in the change data source, thereby realizing data processing of the digital twin system.

[0073] Step S204: Match the digital twin objects in the change data source with the digital twin objects in the original data source to obtain a matching result.

[0074] Among them, the matching result is used to indicate whether the digital twin objects in the change data source and the digital twin objects in the original data source belong to the same digital twin entity.

[0075] In an alternative embodiment, in order to determine whether digital twin objects belong to the same digital twin entity, the identification information of the digital twin objects in the original data source can be compared with the identification information of the digital twin objects in the change data source. If the two identification information is the same, it means that the digital twin objects in the original data source and the change data source belong to the same digital twin entity; if the two identification information is different, that is, the digital twin objects included in the change data source are not recorded in the original data source, it means that the change data source has added digital twin objects, and the original data source can be changed according to the newly added digital twin objects.

[0076] In another alternative embodiment, to determine whether digital twin objects belong to the same digital twin entity, the object attributes of the digital twin objects in the original digital source can be compared with the object attributes of the digital twin objects in the change data source. If the similarity of the object attributes of the digital twin objects in the two data sources is greater than or equal to a preset value, it indicates that the digital twin objects in the original data source and the change data source belong to the same digital twin entity. If the similarity of the object attributes of the digital twin objects in the two data sources is less than the preset value, that is, the digital twin objects included in the change data source are not recorded in the original data source, it indicates that new digital twin objects have been added to the change data source, and the original data source can be changed according to the newly added digital twin objects.

[0077] Figure 3 is a schematic diagram of digital twin object matching according to an embodiment of the present application, as Figure 3 shown, data source 1 can be the original data source, and data source 2 can be the change data source. The data of data source 1 and data source 2 can be preprocessed respectively to obtain the preprocessed data. Optionally, the data can be preprocessed by means such as data cleaning, deduplication, and conversion. The preprocessing method of the data is not limited here and can be determined according to the situation. Multiple models are involved in the matching process, including a space model, a geometric model, a relationship model, a task model, a behavior model, and an index model.

[0078] Among them, the spatial model is used to determine the spatial position similarity based on the coordinate points of the data in Data Source 1 and Data Source 2, and obtain the first similarity determination result. The geometric model is used to determine the similarity based on the geometric contours of the data in Data Source 1 and Data Source 2, and obtain the second similarity determination result. The relationship model is used to determine the similarity based on the connection relationships between the digital twin objects in Data Source 1 and Data Source 2 and the remaining associated objects, and obtain the third similarity determination result. The task model is used to determine the similarity based on the characteristic attributes of the industries to which the digital twin objects in Data Source 1 and Data Source 2 belong, and obtain the fourth similarity determination result. The behavior model is used to determine the similarity based on the object capabilities of the digital twin objects in Data Source 1 and Data Source 2, and obtain the fifth similarity determination result. The index model is used to determine the similarity based on the object dynamic indexes of the digital twin objects in Data Source 1 and Data Source 2, and obtain the sixth similarity determination result. It is possible to perform similarity ranking on the digital twin objects in Data Source 1 and the digital twin objects in Data Source 2 based on any one or more of the first similarity determination result, the second similarity determination result, the third similarity determination result, the fourth similarity determination result, the fifth similarity determination result, and the sixth similarity determination result, and obtain a ranking result. Among them, the ranking order can be determined according to the similarity between the digital twin objects in Data Source 1 and Data Source 2. The digital twin objects in Data Source 1 and Data Source 2 with a higher ranking have a greater similarity, and the digital twin objects in Data Source 1 and Data Source 2 with a lower ranking have a smaller similarity. The specific ranking result can be set according to requirements. It is also possible to rank the results with a greater similarity in the front and rank the results with a smaller similarity in the back.

[0079] Furthermore, the above-mentioned matching result can be determined according to the ranking result. When sorting in the order of decreasing similarity, it can be determined that the first preset number of digital twin objects in Data Source 1 and Data Source 2 before sorting match successfully, and the digital twin objects with a lower ranking fail to match. When sorting in the order of increasing similarity, it can be determined that the first preset number of digital twin objects in Data Source 1 and Data Source 2 before sorting fail to match, and the digital twin objects with a lower ranking match successfully.

[0080] It should be noted that the spatial model is used to determine spatial similarity based on coordinate points. The associated objects in the relationship model include, but are not limited to, associated personnel, associated regions, associated cases, and associated representatives. The characteristic attributes of the industry in the task model include, but are not limited to, national standard industry, unified social credit code, registered address, enterprise name, registered capital, organization code, industrial and commercial registration number, enterprise type, establishment date, and personnel scale. The object capabilities in the behavior model include, but are not limited to, contract capabilities, litigation capabilities, tax payment capabilities, and borrowing capabilities. The object dynamic indicators in the indicator model include, but are not limited to, registration status, risk status, debt status, and public opinion status.

[0081] Step S206: Based on the change type of the change data source and the matching result, change the object attribute value of the digital twin object in the original data source to obtain a first change result.

[0082] The above change types can be slow change types and fast change types. Among them, the slow change type refers to the situation where the attribute value remains relatively stable for a long time. In this case, the change of the attribute value is gradual, changing with a small amplitude and frequency. For example, attributes such as a person's gender and height are usually slowly changing because they usually remain relatively stable for a long time. The above fast change type refers to the situation where the attribute value changes frequently in a short time. In this case, the change of the attribute value is sudden and large. For example, attributes such as stock prices and weather conditions are usually fast changing because they may change multiple times in a short time.

[0083] The above first change result is used to indicate whether the object attribute value of the digital twin object in the original data source has been successfully changed. Optionally, the first change result can be sent to the client device so that the user of the client device can timely understand the change situation of the original data source in the digital twin system.

[0084] If the matching result indicates that the digital twin object in the change data source and the digital twin object in the original data source belong to the same digital twin entity, it means that the change data source is to change the object attribute value of the existing digital twin object in the original data source. The object attribute value of the digital twin object in the original data source can be replaced with the object attribute value of the digital twin object belonging to the same digital twin entity in the change data source.

[0085] If the matching result indicates that the digital twin object in the change data source and the digital twin object in the original data source do not belong to the same digital twin entity, it means that the change data source is used to add a new digital twin object and the object attribute value of the new digital twin object. The new digital twin object and the object attribute value of the new digital twin object can be added to the original data source.

[0086] For the data source of changes to slowly changing attributes, the details of the changes can be recorded in the detailed change list of the Operational DataStore (ODS) entity.

[0087] For the data source of changes to rapidly changing attributes, the object attribute values within a certain time period in the data source of changes can be obtained, and based on these object attribute values, the object attribute values of the original data source are changed to obtain a first change result.

[0088] Through the above steps, first, a data processing instruction is received, and the original data source and the data source of changes of the digital twin system are obtained; the digital twin objects in the data source of changes are matched with the digital twin objects in the original data source to obtain a matching result, where the matching result is used to indicate whether the digital twin objects in the data source of changes and the digital twin objects in the original data source belong to the same digital twin entity; based on the change type of the data source of changes and the matching result, the object attribute values of the digital twin objects in the original data source are changed to obtain a first change result, achieving an improvement in the management efficiency of attribute changes in the digital twin system. It is easy to notice that matching can be performed on different types of digital twin objects in the received data source of changes, so that the object attribute values of the digital twin objects in the original data source are changed according to the object attribute values of the digital twin objects in the data source of changes, so that the attribute changes of the digital twin objects are consistent, enabling the digital twin objects to display the same object attribute values among different users. Through the matching method, the object attribute values corresponding to the digital twin objects can be updated, thereby improving the management efficiency of attribute changes and solving the technical problem of poor management efficiency of attribute changes in the digital twin system in the related art.

[0089] In the above embodiments of the present application, changing the object attribute values of the digital twin objects in the original data source based on the change type of the data source of changes and the matching result to obtain a first change result includes: if the matching result is that the digital twin objects in the data source of changes and the digital twin objects in the original data source belong to the same digital twin entity, changing the entity information record table in the original data source based on the change type of the data source of changes and the first object attribute value of the digital twin object in the data source of changes to obtain a first change result, where the entity information record table is used to represent the information record table for the digital twin entity; if the matching result is that the digital twin objects in the data source of changes and the digital twin objects in the original data source correspond to different digital twin entities, changing the entity information record table based on the change type of the data source of changes and the second object attribute value of the digital twin object and the digital twin object in the data source of changes to obtain a first change result.

[0090] The above-mentioned entity information record table can be the entity basic information table of the Data Warehouse Detail (DWD for short).

[0091] The relevant information of the above-mentioned original data source can be recorded in the entity basic information table of the Data Warehouse Detail (DWD for short). The digital twin objects in the changed data source can be matched with the digital twin objects recorded in the entity basic information table to determine the association relationship between the digital twin objects in the changed data source and the entity data source.

[0092] For the changed data source with slowly changing attributes, the digital twin objects in the changed data source can be matched with the digital twin objects recorded in the entity basic information table. If the match is successful, the object attribute values of the digital twin objects in the changed data source can be compared with the object attribute values of the digital twin objects recorded in the entity basic information table. If the object attribute values are inconsistent, it indicates that the attribute values of the existing digital twin objects have changed. If the object attribute values are consistent, it indicates that the attribute values of the existing digital twin objects have not changed.

[0093] Furthermore, if the match fails, it can be determined that the digital twin objects in the changed data source are newly added digital twin objects.

[0094] For the changed data source with rapidly changing attributes, the above-mentioned matching method can also be used for matching, which will not be elaborated here. Since the data of the changed data source with rapidly changing attributes changes relatively fast, generally, the matching results need to be stored in advance. When used, the digital twin objects in the original data source and the digital twin objects in the changed data source can be directly matched by means of equal value matching, so as to improve the matching speed and then ensure the processing efficiency of real-time data.

[0095] The core principle of the above-mentioned matching is based on the similarity of digital twin objects to determine whether the two digital twin objects in the changed data source and the original data source represent the same digital twin entity in the real world.

[0096] In an alternative embodiment, if the matching result indicates that the digital twin object in the change data source and the digital twin object in the original data source belong to the same digital twin entity, the object attribute value of the digital twin object recorded in the entity basic information table of the data warehouse detail layer (abbreviated as DWD) is changed based on the first object attribute value of the digital twin object in the change data source. The change status can be to update the object attribute value of the digital twin object that already exists in the original data source. Optionally, the object attribute value can be changed to the first object attribute value corresponding to the digital twin object in the change data source, thereby obtaining a first change result.

[0097] If the matching result indicates that the digital twin object in the change data source and the digital twin object in the original data source correspond to different digital twin entities, the digital twin object and the second object attribute value of the digital twin object in the change data source are added to the entity basic information table in the DWD layer, thereby obtaining a second change result.

[0098] The above-mentioned first object attribute value can be the attribute value of the original digital twin object in the original data source, and the above-mentioned second object attribute value can be the attribute value of the newly added digital twin object.

[0099] In the above embodiments of the present application, the entity information record table in the original data source is changed based on the change type of the change data source and the first object attribute value of the digital twin object in the change data source to obtain a first change result, including: if the change type is the first change type, the current object attribute value of the digital twin object in the entity information record table is replaced based on the first object attribute value to obtain a first change result; if the change type is the second change type, the current object attribute value of the digital twin object in the entity information record table is replaced based on the time period granularity of the change data source and the first object attribute value to obtain a first change result, where the time period granularity is used to represent the division granularity of the total time period of the change data source, and the second change type and the first change type are used to distinguish change data sources with different change speeds.

[0100] The above-mentioned first change type can be a slow change type, and the above-mentioned second change type can be a fast change type.

[0101] The change data source of the first change type can include non-real-time data of external data sources, algorithmically batch-generated objects, manually revised objects on pages, and event information associated with objects.

[0102] The above-mentioned entity information record table can also be the details of the changes recorded in the entity change detail table of the operational data store (abbreviated as ODS).

[0103] Among them, the non-real-time data of the external data source is the data obtained by a single call to the application programming interface (API) of a third-party data provider, or the discrete moment data related to the object attributes obtained from other types of data sources.

[0104] The batch of objects generated by the algorithm is a batch of digital twin object data generated based on a single algorithm execution task.

[0105] The object revised manually on the page is the addition, deletion, and attribute correction of digital twin objects implemented based on the object management visualization page of the digital twin system.

[0106] The event information associated with the object is an event generated by the digital twin object itself or an event associated with it, and the occurrence of the event has caused a change in the object's attributes or the birth / death of life.

[0107] The change data source of the second change type may include external data source real-time data, sensor data, and Internet of Things data.

[0108] The external data source real-time data is real-time data from the external environment or a third-party API. For example, real-time meteorological data, real-time traffic data, etc.

[0109] Sensor data refers to the real-time sensor index data obtained by connecting the digital twin system and sensor devices. Common sensors include temperature sensors, humidity sensors, and pressure sensors, etc.

[0110] The Internet of Things data is the data collected and reported by Internet of Things devices. Common Internet of Things devices include: smart home devices, smart factory devices, smart monitoring devices, etc.

[0111] In an optional embodiment, if the change data source belongs to the first change type, the current object attribute value of the digital twin object in the entity information record table can be replaced based on the first object attribute value to obtain an initial change result. After obtaining the initial change result, the change details of the initial change result can be recorded in the ODS entity change details table, and the ODS entity change details table includes entity basic attributes, data status, change status, associated source, and creation time.

[0112] Among them, the entity basic attributes correspond to the attributes recorded in the DWD layer entity information basic table. The changed attributes can store the changed object attribute values, and the unchanged attributes can store the attribute values of the latest data of this object in the ODS layer entity change details table.

[0113] The data status can be used to determine whether the above-mentioned change process is effective through an approval operation. Generally, the approval operation can be initiated by the operation and maintenance personnel of the data source department. Only when the approval is passed, it is considered that this change is effective, and then it enters the subsequent processing process.

[0114] The change status can be used to express the change situation of the data in this row, including adding an object, deleting an object, and changing the attributes of an existing object.

[0115] The change status is used to express the change situation of the data in this row, including adding an object, deleting an object, and changing the attributes of an existing object.

[0116] The associated source identifies the specific information of the source of the changed attribute. For example, external data source identification information (IdentityDocument, abbreviated as ID), algorithm execution task ID, manual revision task ID, associated event ID, etc.

[0117] The creation time is the time when the data in this row is written, and the format is YYYY-MM-DD or HH:MI:SS. This is only an example here and is not limited to this.

[0118] The total time period of the above-mentioned changed data source is determined based on the first time point when data starts to be received and the second time point when data reception is completed in the changed data source.

[0119] The above time period granularity is used to represent the division size of the total time period. Among them, the total time period can be evenly divided into multiple periods according to the time period granularity. The larger the division granularity, the larger the divided part, and the fewer the number of divided periods. The smaller the division granularity, the smaller the divided part, and the more the number of divided periods.

[0120] In another alternative embodiment, if the changed data source belongs to the second change type, since the data of the fast change type changes rapidly, resulting in a relatively high update frequency, there may be multiple versions of the object attribute values of the digital twin object in the changed data source. After dividing the changed data source based on the time period granularity of the changed data source, the data in different time periods in the changed data source can be obtained. The current object attribute value of the digital twin object in the entity information record table can be replaced according to the object attribute values included in the data within the predetermined time period to obtain the first change result.

[0121] In the above embodiments of the present application, the current object attribute value of the digital twin object in the entity information record table is replaced based on the time period granularity of the changed data source and the first object attribute value to obtain a first change result, including: dividing the total time period based on the time period granularity to obtain a plurality of time windows; determining sub-object attribute values according to the first object attribute value and the plurality of time windows; replacing the current object attribute value of the digital twin object based on the sub-object attribute values to obtain a first change result.

[0122] The above-mentioned plurality of time windows can be arranged according to the time sequence of the changed data source.

[0123] The above-mentioned sub-object attribute values can be used to represent the first object attribute values included in any one or more of the plurality of time windows.

[0124] In an alternative embodiment, the sub-object attribute value in the first object attribute can be determined according to the first object attribute value and the plurality of time windows. The sub-object attribute value can be expressed as the object attribute value obtained by the latest update. The current object attribute value of the digital twin object can be replaced according to the sub-object attribute value to obtain a first change result.

[0125] In the above embodiments of the present application, determining the sub-object attribute value according to the first object attribute value and the plurality of time windows includes: determining whether there is a first object attribute value in the first time window among the plurality of time windows, where the first time window is the last time window in the total time period; if there is a first object attribute value in the first time window, determining the sub-object attribute value corresponding to the first time window according to the first object attribute value; if there is no first object attribute value in the first time window, determining the sub-object attribute value corresponding to the second time window according to the first object attribute value, where the second time window is the time window adjacent to the first time window.

[0126] In an alternative embodiment, it can be determined whether there is a first object attribute value in the last time window of the total time period. If it exists, the sub-object attribute value corresponding to the first time window can be determined according to the first object attribute value. If it does not exist, the sub-object attribute value corresponding to the second time window can be determined according to the second object attribute value, so as to determine the object attribute value obtained by the latest update.

[0127] Furthermore, if there is no first object attribute value in the second time window, it can be determined whether there is a first object attribute value in the third time window adjacent to the second time window, and so on until a time window with a first object attribute value is obtained, and the sub-object attribute value in this time window is determined to ensure the continuity and integrity of the time period.

[0128] In the above embodiments of the present application, the method further includes: processing the total time period by using a target neural network model to obtain a time period granularity.

[0129] The above target neural network model may be a convolutional neural network model, but is not limited thereto.

[0130] The above digital twin system can support automatic analysis of the attribute update frequency for a specified test data set. The core idea is to find a time period granularity through an algorithm to cover the object attribute values above a specified coverage ratio within the total time period.

[0131] In an alternative embodiment, the total time period may be processed by using a target neural network model to obtain a time period granularity. It should be noted that the coverage ratio obtained from the total time period and the time period granularity is a preset coverage ratio, where the coverage ratio may be the ratio between the number of time windows containing the first object attribute value and the total number of time windows.

[0132] In the above embodiments of the present application, the method further includes: processing the total time period by using an initial neural network model to obtain a first time period granularity; dividing the total time period based on the first time period granularity to obtain a plurality of sample time windows; determining the coverage ratio of the target sample time window according to the first number of the plurality of sample time windows and the second number of the target sample time window, where the target sample time window is a sample time window among the plurality of sample time windows that contains the first object attribute value; constructing a loss function based on the coverage ratio and the preset coverage ratio; adjusting the model parameters of the initial neural network model by using the loss function to obtain a target neural network model, where the target neural network model is used to process the total time period to obtain a time period granularity.

[0133] The above preset coverage ratio may be a pre-configured coverage ratio.

[0134] First, the total time period may be processed by using an initial neural network model to obtain a first time period granularity. The accuracy of the first time period granularity needs to be improved. The total time period may be divided based on the first time period granularity to obtain a plurality of sample time windows. The first number of the plurality of sample time windows and the second number of the target sample time window may be determined. The coverage ratio of the target sample time window in the plurality of sample time windows may be determined according to the ratio of the first number and the second number. A loss function may be constructed based on the coverage ratio and the preset coverage ratio to adjust the obtained first time period granularity through the backpropagation algorithm so that the obtained coverage ratio tends to the configured value.

[0135] In the above embodiments of the present application, the method further includes: updating the snapshot fact table of the digital twin system based on the first change result, where the snapshot fact table is used to represent the information record table for the digital twin object.

[0136] The above-mentioned snapshot fact table is used to record the change information of the digital twin object. Among them, the snapshot fact table includes but is not limited to the cumulative snapshot fact table for the digital twin object, the cumulative snapshot fact table for the digital twin object attributes, and the periodic snapshot fact table for the digital twin object attributes.

[0137] For the change data source of the slowly changing attribute, if the change data source is to add or delete a digital twin object, the cumulative snapshot fact table for the digital twin object can be used, so as to clearly record the life cycle of the digital twin object. The progress of the digital twin object can be recorded through the "object birth time" and "object death time" fields, and the same data supports updates at different time points.

[0138] The cumulative snapshot fact table for the digital twin object contains the unique identifier of the entity type, the name of the DWD layer entity basic information table, the unique identifier of the object, the object birth time, the object death time, the object birth details, and the object death details.

[0139] The unique identifier of the entity type is the unique identifier of the digital twin entity to which the digital twin object belongs.

[0140] The name of the DWD layer entity basic information table is used to represent the name of the digital twin entity basic information table.

[0141] The unique identifier of the object is the unique identifier of the digital twin object.

[0142] The object birth time is when the value of the "change status" field is "new object", a new row of data is added, and this field is assigned a value.

[0143] The object death time is when the value of the "change status" field is "delete object", query the object data row based on the "unique identifier of the object", and update the value of this field, which is default NULL.

[0144] The object birth details are the facts of the snapshot table, which are in a custom format by the task and can record information such as the reason for the object birth.

[0145] The object death details are the facts of the snapshot table, which are in a custom format by the task and can record information such as the reason for the object death.

[0146] For the change data source of slowly changing attributes, if the change data source is the object attributes of the digital twin object, a cumulative snapshot fact table for digital twin object attributes can be adopted to clearly record the life cycle of each attribute value of the digital twin object. Through the "start time" and "end time" fields, the situation of the attribute values of the digital twin object is recorded, and the same data supports updates at different time points.

[0147] The cumulative snapshot fact table for digital twin object attributes includes the unique identifier of the entity type, the name of the entity basic information table in the DWD layer, the unique identifier of the object, the unique identifier of the attribute, the attribute value, the associated source, the start time of the time window, and the end time of the time window.

[0148] The unique identifier of the entity type is the unique identifier of the digital twin entity to which the digital twin object belongs.

[0149] The name of the entity basic information table in the DWD layer is the name of the digital twin entity basic information table.

[0150] The unique identifier of the object is the unique identifier of the digital twin object.

[0151] The unique identifier of the attribute is the unique identifier of the attribute of the digital twin object. For example, the device name (devc_name).

[0152] The attribute value is the specific value of the attribute of the digital twin object.

[0153] The associated source is used to record the source of the attribute change. For example, the external data source ID, the algorithm execution task ID, the manual revision task ID, and the associated event ID.

[0154] The start time can be the attribute change time of the digital twin object when a new digital twin object is added. When a new digital twin object is added, a new row will be added to this table for each object attribute value of the digital twin object, and the value of this column will be generated at this time; when the object attribute value of the digital twin object changes, a new row will be added to this table for the attribute whose attribute value has changed, and the value of this column will be generated at this time.

[0155] The end time can be the attribute change time when the attribute value of the digital twin object changes. Query the data with "end time" being NULL based on the object unique identifier and the attribute unique identifier, and assign a value to its "end time" field.

[0156] Figure 4 It is a schematic diagram of a data processing mechanism for slowly changing attributes according to an embodiment of the present application, as Figure 4As shown, the sources of the change data sources for slow-changing attributes include non-real-time data from external data sources, algorithmically batch-generated objects, manually revised objects on the page, and event information associated with the objects. Data cleaning can be performed on the data in the change data sources to determine the object attribute change information of the digital twin objects. In the identification mapping layer, the cleaned change data sources are matched with the digital twin objects in the original data sources recorded in the DWD layer entity basic information table to obtain the association relationship between the digital twin objects in the change data sources and the original data sources, and the change status can be determined. The specific details of the changes can be recorded in the ODS layer entity change details table. The changed data can be audited in the data status to obtain a status of valid change or invalid change. If the data status is a valid change, the cumulative snapshot fact table to be changed is determined according to the change status. If the change status is a new object or a deleted object, the cumulative snapshot fact table for the digital twin objects can be modified. If the change status is a change in the attributes of an existing object, the cumulative snapshot fact table for the attributes of the digital twin objects can be modified.

[0157] For the change data sources of fast-changing attributes, a periodic snapshot fact table for the attributes of digital twin objects can be used. The periodic snapshot fact table records facts at regular and predictable time intervals. In the digital twin system, the attribute values of digital twin objects are stored periodically as facts. Since they are fast-changing attributes, high-frequency writes to the fact table are required, so a periodic snapshot fact table is used.

[0158] The periodic snapshot fact table for the attributes of digital twin objects includes entity type, time window size, object unique identifier, attribute unique identifier, attribute value, association source, start time of the time window, and end time of the time window.

[0159] The entity type unique identifier is the unique identifier of the digital twin entity to which the digital twin object belongs.

[0160] The time window size is such that the time window type uses a rolling window and the periods do not overlap.

[0161] The object unique identifier is the unique identifier of the digital twin object.

[0162] The attribute unique identifier is the unique identifier of the attribute of the digital twin object, for example, the device name.

[0163] The attribute value is the specific value of the attribute of the digital twin object.

[0164] The association source is used to record the source of the attribute change, such as: external data source ID / sensor device ID / Internet of Things system ID, etc.

[0165] The start time and end time of the time window are generated together, in the format: YYYY-MM-DD HH:MI:SS, but not limited to this.

[0166] The end time of the time window is generated together with the start time of the time window, in the format: YYYY-MM-DD HH:MI:SS, but not limited to this.

[0167] Figure 5 is a schematic diagram of a data processing mechanism for rapidly changing attributes according to an embodiment of the present application. As Figure 5 shown, the change data source of the rapidly changing attribute comes from external data source real-time data, sensor data, and Internet of Things data. Data cleaning can be performed on the data in the change data source to determine the object attribute change information of the digital twin object. In the identity mapping layer, the cleaned change data source is matched with the digital twin object in the original data source recorded in the DWD layer entity basic information table to obtain the association relationship between the digital twin objects in the change data source and the original data source, so as to determine the attribute change information. The attribute update frequency characteristics of the data in the change data source can be analyzed to determine multiple time windows, and the latest attribute value of the current time window is determined according to the multiple time windows and the attribute change information, and the periodic snapshot fact table for the digital twin object attribute is updated according to the latest attribute value. It should be noted that when there is no attribute in the current time window, the attribute value of the previous time window can be taken as the attribute value of the current time window to ensure the continuity and integrity of the time period.

[0168] In the above embodiments of the present application, the method further includes: receiving a page display instruction acting on the interaction interface, and displaying a target page on the interaction interface, where the target page is used to display at least one of the following: the current attribute information of the digital twin object, the attribute time series information of the digital twin object. The current attribute information is generated based on the entity information record table, and the attribute time series information is generated based on the snapshot fact table.

[0169] The above current attribute information of the digital twin object includes but is not limited to the current static attribute display page of the digital twin object and the digital twin object life cycle management page.

[0170] The above attribute time series information of the digital twin object includes but is not limited to the static attribute time series diagram page of the digital twin object and the dynamic attribute time series diagram page of the digital twin object.

[0171] Figure 6 is a schematic diagram of a digital twin object management page according to an embodiment of the present application. As Figure 6 shown, it includes the current static attribute display page of the digital twin object, the digital twin object life cycle management page, the static attribute time series diagram page of the digital twin object, and the dynamic attribute time series diagram page of the digital twin object.

[0172] For the current static property display page of the above digital twin object, in the entity change detail list in the ODS layer, the full amount of property information after the change of different digital twin objects is stored. Therefore, the latest data rows of different digital twin objects can be retrieved to support the display of the current static properties of the object in the digital twin object management page.

[0173] For the above digital twin object lifecycle management page, in the cumulative snapshot fact table for digital twin objects, the object birth time and object death time of different digital twin objects are stored to support the display of the lifecycles of different digital twin objects in the digital twin object management page.

[0174] For the above static property time series diagram of the digital twin object, for a specific property of a certain digital twin object, data filtering can be performed through the cumulative snapshot fact table for digital twin object properties based on the object unique identifier and the property unique identifier, and sorted by the start time to obtain a time series diagram with the property value as the Y-axis and the time value as the X-axis.

[0175] For the above dynamic property time series diagram of the digital twin object: for a specific property of a certain digital twin object, data filtering can be performed through the periodic snapshot fact table for digital random object properties based on the object unique identifier and the property unique identifier, and sorted by the start time of the time window to obtain a time series diagram with the property value as the Y-axis and the time value as the X-axis.

[0176] In the above embodiments of the present application, the method further includes: receiving a selection instruction for the property time series information in the target page, determining the historical property value of the digital twin object corresponding to the selection instruction in the property time series information; and changing the entity information record table based on the historical property value to obtain a second change result.

[0177] In the digital twin management page, the user can view the static property time series diagram of the digital twin object. If it is necessary to restore to the historical property value, the historical property value in the time series diagram can be selected for the property restoration rollback operation to generate a selection instruction. The historical property value selected by the user can be determined according to the generated instruction, and the entity information record table can be changed according to the historical property value to obtain a second change result. This operation is equivalent to manually revising the properties of the digital twin object on the page.

[0178] Figure 7 It is a schematic diagram of a restoration rollback mechanism according to an embodiment of the present application, as Figure 7As shown, in the digital twin management page, the time series diagram of the static attributes of the digital twin object can be viewed. At this time, the historical attribute values in the time series diagram can be selected for attribute restoration and rollback. This operation is equivalent to manually revising the attributes of the digital twin object on the page, that is, the page manual revision object in the figure.

[0179] In the above embodiments of the present application, the method further includes: using a prediction model to predict the change time point of the digital twin system based on a preset time interval to obtain a target time series diagram, where the target time series diagram is used to represent the correspondence between the predicted attribute values of the prediction object and the change time points of the predicted attribute values of the prediction object within the preset time interval.

[0180] The above preset time interval can be a preset time interval for predicting information changes in the digital twin system.

[0181] The horizontal axis in the above target time series diagram can be the predicted time value, and the vertical axis can be the attribute prediction value.

[0182] The above prediction model can be an attribute fitting model or a neural network model, and no limitation is imposed on the type of the prediction model here.

[0183] In an alternative embodiment, if the user needs to preset the change time point of the digital twin system within a preset time interval, the prediction model can be used to predict the change time point of the digital twin system based on the preset time interval to obtain a target time series diagram.

[0184] In the above embodiments of the present application, the method further includes: obtaining the sample change time points in the target time interval and the sample object attribute values corresponding to the sample change time points in the snapshot fact table; determining the actual time series diagram of the target time interval based on the sample change time points and the sample object attribute values; using an initial prediction model to predict the sample change time points based on the target time interval to obtain a predicted time series diagram; adjusting the model parameters of the initial prediction model based on the predicted time series diagram and the actual time series diagram to obtain a prediction model.

[0185] The above snapshot fact table can be an accumulated snapshot fact table for digital twin object attributes and / or a periodic snapshot fact table for digital twin object attributes, and no limitation is imposed here.

[0186] In an alternative embodiment, the moment value and the attribute value in the snapshot fact table can be read. The moment value is the sample change time point described above, and the attribute value is the sample object attribute value described above, forming a sequence of attribute value change data based on time order, that is, the actual time series diagram described above. The initial prediction model can be used to predict the sample change time point based on the target time interval to obtain a predicted time series diagram. A loss function can be constructed according to the predicted time series diagram and the actual time series diagram, and the model parameters of the initial prediction model can be adjusted according to the loss function to obtain a prediction model.

[0187] Figure 8 It is a schematic diagram of an attribute change prediction model according to an embodiment of the present application. As Figure 8 shown, the cumulative snapshot fact table for the digital twin object attribute, the periodic snapshot fact table for the digital twin object attribute, and the association information between the moment value and the attribute value in the specified attribute of the specified digital twin object can be passed into the attribute fitting model. A linear function of the first order or a linear function with a custom order can be used in the attribute fitting model, and the attribute fitting model can be calculated. Optionally, methods such as the least squares method, maximum likelihood estimation, curve fitting, and neural network can be used to calculate the attribute fitting model to obtain a final prediction model. The prediction time interval can be configured to obtain the predicted object attribute value and the change time point of the predicted object attribute value, and the predicted time series diagram can be displayed according to the predicted object attribute value and the change time point of the predicted object attribute value.

[0188] In the present application, a set of general data processing and storage solutions are designed and implemented. By combining the design solution of the cumulative snapshot fact table in the digital warehouse, for different types of digital twin entities and specific digital twin objects, the changes of their slowly changing static attributes are recorded, and subsequent change detail queries and simulation deduction operations are conveniently supported. A set of general data processing and storage solutions are designed and implemented. By combining the design solution of the periodic snapshot fact table in the digital warehouse, for different types of digital twin entities and specific digital twin objects, the changes of their rapidly changing dynamic attributes are recorded, and subsequent change detail queries and simulation deduction operations are conveniently supported. A set of general recovery and rollback mechanisms are designed and implemented. When errors and accidents occur, operators are supported to restore the historical version attributes of digital twin objects. A set of general attribute change prediction models are designed and implemented. Based on the historical change characteristics of attributes, predicted attribute values for a future specified time period are provided.

[0189] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties. Moreover, the collection, use, and processing of relevant data need to comply with the relevant laws, regulations, and standards of relevant countries and regions, and corresponding operation entrances are provided for users to choose to authorize or refuse.

[0190] It should be noted that for the foregoing method embodiments, for the sake of simple description, they are all expressed as a series of action combinations. However, those skilled in the art should know that this application is not limited by the described action sequence, because according to this application, certain steps can be performed in other sequences or simultaneously. Secondly, those skilled in the art should also know that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily essential to this application.

[0191] Through the description of the above embodiments, those skilled in the art can clearly understand that the method according to the above embodiments can be implemented by means of software plus a necessary general hardware platform, and of course, it can also be implemented by hardware. Based on such an understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk), and includes several instructions for causing a terminal device (which can be a mobile phone, computer, server, or network device, etc.) to execute the methods of various embodiments of this application.

[0192] Embodiment 2

[0193] According to an embodiment of this application, a data processing method for a digital twin system is further provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. And although the logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in a different order than this.

[0194] Figure 9 is a flowchart of a data processing method for a digital twin system according to Embodiment 2 of this application. As Figure 9 shown, the method includes the following steps:

[0195] Step S902, in response to an operation instruction acting on the operation interface, display the original data source and the changed data source of the digital twin system on the operation interface.

[0196] Among them, the digital twin system is used to manage digital twin entities in the real world through digital twin objects in the virtual world.

[0197] Step S904: In response to a processing instruction acting on the operation interface, display a first change result on the operation interface.

[0198] Among them, the first change result is obtained by changing the object attribute value of the digital twin object in the original data source based on the change type of the change data source and the matching result. The matching result is obtained by matching the digital twin object in the change data source with the digital twin object in the original data source. The matching result is used to indicate whether the digital twin object in the change data source and the digital twin object in the original data source belong to the same digital twin entity.

[0199] Through the above steps, in response to an operation instruction acting on the operation interface, display the original data source and the change data source of the digital twin system on the operation interface; in response to a processing instruction acting on the operation interface, display a first change result on the operation interface. Among them, the first change result is obtained by changing the object attribute value of the digital twin object in the original data source based on the change type of the change data source and the matching result. The matching result is obtained by matching the digital twin object in the change data source with the digital twin object in the original data source. The matching result is used to indicate whether the digital twin object in the change data source and the digital twin object in the original data source belong to the same digital twin entity, which improves the management efficiency of attribute changes in the digital twin system. It is easy to notice that matching can be performed on different types of digital twin objects in the received change data source, so as to change the object attribute value of the digital twin object in the original data source according to the object attribute value of the digital twin object in the change data source, so that the attribute changes of the digital twin object are consistent, and the digital twin object can display the same object attribute value among different users. By matching, the object attribute value corresponding to the digital twin object can be updated, thereby improving the management efficiency of attribute changes, and further solving the technical problem of poor management efficiency of attribute changes in the digital twin system in the related art.

[0200] It should be noted that the preferred implementation schemes involved in the above embodiments of the present application are the same as the schemes, application scenarios, and implementation processes provided in Embodiment 1, but are not limited to the schemes provided in Embodiment 1.

[0201] Embodiment 3

[0202] According to an embodiment of the present application, a data processing method for a digital twin system is further provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. And, although the logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in a different order than this.

[0203] Figure 10 is a flowchart of a data processing method of a digital twin system according to Embodiment 3 of the present application. As Figure 10 shown, the method includes the following steps:

[0204] Step S1002, in response to receiving a data processing instruction for the digital twin system, receiving the data processing instruction by calling a first interface, and obtaining the original data source and the changed data source of the digital twin system.

[0205] Among them, the digital twin system is used to manage digital twin entities in the real world through digital twin objects in the virtual world. The first interface includes a first parameter, and the parameter value of the first parameter is the original data source and the changed data source.

[0206] Step S1004, matching the digital twin objects in the changed data source with the digital twin objects in the original data source to obtain a matching result.

[0207] Among them, the matching result is used to indicate whether the digital twin objects in the changed data source and the digital twin objects in the original data source belong to the same digital twin entity.

[0208] Step S1006, changing the object attribute values of the digital twin objects in the original data source based on the change type of the changed data source and the matching result to obtain a first change result.

[0209] Step S1008, outputting the first change result by calling a second interface.

[0210] Among them, the second interface includes a second parameter, and the parameter value of the second parameter is the first change result.

[0211] Through the above steps, in response to receiving a data processing instruction for the digital twin system, the original data source and the change data source of the digital twin system are obtained by calling the first interface, where the first interface includes a first parameter, and the parameter value of the first parameter is the original data source and the change data source; the digital twin objects in the change data source are matched with the digital twin objects in the original data source to obtain a matching result, where the matching result is used to indicate whether the digital twin objects in the change data source and the digital twin objects in the original data source belong to the same digital twin entity; the object attribute values of the digital twin objects in the original data source are changed based on the change type of the change data source and the matching result to obtain a first change result; the first change result is output by calling the second interface, where the second interface includes a second parameter, and the parameter value of the second parameter is the first change result, which improves the management efficiency of attribute changes in the digital twin system. It is easy to notice that matching can be performed on different types of digital twin objects in the received change data source, so as to change the object attribute values of the digital twin objects in the original data source according to the object attribute values of the digital twin objects in the change data source, so that the attribute changes of the digital twin objects are consistent, and the digital twin objects can display the same object attribute values among different users. Through the matching method, the object attribute values corresponding to the digital twin objects can be updated, thereby improving the management efficiency of attribute changes, and further solving the technical problem of poor management efficiency of attribute changes in the digital twin system in the related art.

[0212] It should be noted that the preferred implementation schemes involved in the above embodiments of the present application are the same as the schemes, application scenarios, and implementation processes provided in Embodiment 1, but are not limited to the schemes provided in Embodiment 1.

[0213] Embodiment 4

[0214] According to an embodiment of the present application, there is also provided a data processing device for a digital twin system for implementing the data processing method of the above digital twin system. Figure 11 It is a schematic diagram of a data processing device for a digital twin system according to an embodiment of the present application, as Figure 11 shown. The device 1100 includes: a receiving module 1102, a matching module 1104, and a change module 1106.

[0215] Among them, the receiving module is used to receive a data processing instruction and obtain the original data source and the changed data source of the digital twin system; the matching module is used to match the digital twin objects in the changed data source with the digital twin objects in the original data source to obtain a matching result, where the matching result is used to indicate whether the digital twin objects in the changed data source and the digital twin objects in the original data source belong to the same digital twin entity; the change module is used to change the object attribute values of the digital twin objects in the original data source based on the change type of the changed data source and the matching result to obtain a first change result.

[0216] It should be noted here that the above receiving module 1102, matching module 1104, and change module 1106 correspond to steps S202 to S206 in Embodiment 1. The examples and application scenarios implemented by the three modules and the corresponding steps are the same, but are not limited to the content disclosed in Embodiment 1 above. It should be noted that the above modules or units can be hardware components or software components stored in a memory (for example, memory 104) and processed by one or more processors (for example, processors 102a, 102b,..., 102n). The above modules can also be part of a device and can run in the computer terminal 10 provided in Embodiment 1.

[0217] In the above embodiments of the present application, the change module is further configured to, when the matching result is that the digital twin objects in the changed data source and the digital twin objects in the original data source belong to the same digital twin entity, change the entity information record table in the original data source based on the change type of the changed data source and the first object attribute value of the digital twin object in the changed data source to obtain a first change result, where the entity information record table is used to represent the information record table for the digital twin entity; when the matching result is that the digital twin objects in the changed data source and the digital twin objects in the original data source correspond to different digital twin entities, change the entity information record table based on the change type of the changed data source and the second object attribute value of the digital twin object and the digital twin object in the changed data source to obtain a first change result.

[0218] In the above embodiments of the present application, the change module is further configured to, when the change type is the first change type, replace the current object attribute value of the digital twin object in the entity information record table with the first object attribute value to obtain a first change result; when the change type is the second change type, replace the current object attribute value of the digital twin object in the entity information record table with the first object attribute value based on the time period granularity of the changed data source to obtain a first change result, where the time period granularity is used to represent the division granularity of the total time period of the changed data source, and the second change type and the first change type are used to distinguish the changed data sources with different change speeds.

[0219] In the above embodiments of the present application, the change module is further configured to divide the total time period based on the time period granularity to obtain a plurality of time windows; determine sub-object attribute values according to the first object attribute value and the plurality of time windows; and replace the current object attribute value of the digital twin object based on the sub-object attribute values to obtain a first change result.

[0220] In the above embodiments of the present application, the change module is further configured to determine whether a first object attribute value exists in a first time window among the plurality of time windows, where the first time window is the last time window in the total time period; if the first object attribute value exists in the first time window, determine the sub-object attribute value corresponding to the first time window according to the first object attribute value; if the first object attribute value does not exist in the first time window, determine the sub-object attribute value corresponding to a second time window according to the first object attribute value, where the second time window is the time window adjacent to the first time window.

[0221] In the above embodiments of the present application, the device further includes: a division module, a determination module, a construction module, and an adjustment module.

[0222] Among them, the processing module is further configured to process the total time period using the initial neural network model to obtain a first time period granularity; the division module is configured to divide the total time period based on the first time period granularity to obtain a plurality of sample time windows; the determination module is configured to determine the coverage ratio of the target sample time window according to the first quantity of the plurality of sample time windows and the second quantity of the target sample time window, where the target sample time window is a sample time window among the plurality of sample time windows that contains the first object attribute value; the construction module is configured to construct a loss function based on the coverage ratio and a preset coverage ratio; the adjustment module is configured to adjust the model parameters of the initial neural network model using the loss function to obtain a target neural network model, where the processing module is further configured to process the total time period using the target neural network model to obtain a time period granularity.

[0223] In the above embodiments of the present application, the device further includes: an update module.

[0224] Among them, the update module is configured to update the snapshot fact table of the digital twin system based on the first change result, where the snapshot fact table is used to represent an information record table for the digital twin object.

[0225] In the above embodiments of the present application, the receiving module is further configured to receive a page display instruction acting on the interaction interface and display a target page on the interaction interface, where the target page is used to display at least one of the following: the current attribute information of the digital twin object, the attribute time series information of the digital twin object, the current attribute information is generated based on the entity information record table, and the attribute time series information is generated based on the snapshot fact table.

[0226] In the above embodiments of the present application, the receiving module is further configured to receive a selection instruction for the attribute time series information in the target page, and determine the historical attribute value of the digital twin object corresponding to the selection instruction in the attribute time series information; and change the entity information record table based on the historical attribute value to obtain a second change result.

[0227] In the above embodiments of the present application, the apparatus further includes: a prediction module.

[0228] Wherein, the prediction module is configured to use a prediction model to predict the change time point of the digital twin system based on a preset time interval to obtain a target time series graph, where the target time series graph is used to represent the corresponding relationship between the predicted object attribute value and the change time point of the predicted object attribute value predicted within the preset time interval.

[0229] In the above embodiments of the present application, the apparatus further includes: an acquisition module.

[0230] Wherein, the acquisition module is configured to acquire the sample change time point in the target time interval and the sample object attribute value corresponding to the sample change time point in the snapshot fact table; the determination module is further configured to determine the actual time series graph of the target time interval based on the sample change time point and the sample object attribute value; the prediction module is further configured to use an initial prediction model to predict the sample change time point based on the target time interval to obtain a predicted time series graph; and the adjustment module is further configured to adjust the model parameters of the initial prediction model based on the predicted time series graph and the actual time series graph to obtain a prediction model.

[0231] It should be noted that the preferred implementation schemes involved in the above embodiments of the present application are the same as the schemes, application scenarios, and implementation processes provided in Embodiment 1, but are not limited to the schemes provided in Embodiment 1.

[0232] Embodiment 5

[0233] According to an embodiment of the present application, there is also provided a data processing apparatus for a digital twin system for implementing the data processing method of the above digital twin system, Figure 12 which is a schematic diagram of a data processing apparatus for a digital twin system according to an embodiment of the present application, as Figure 12 shown, the apparatus 1200 includes: a first display module 1202 and a second display module 1204.

[0234] Among them, the first display module is used to respond to an operation instruction acting on the operation interface and display the original data source and the changed data source of the digital twin system on the operation interface. The digital twin system is used to manage digital twin entities in the real world through digital twin objects in the virtual world. The second display module is used to respond to a processing instruction acting on the operation interface and display a first change result on the operation interface. The first change result is obtained by changing the object attribute values of the digital twin objects in the original data source based on the change type and the matching result of the changed data source. The matching result is obtained by matching the digital twin objects in the changed data source with the digital twin objects in the original data source. The matching result is used to indicate whether the digital twin objects in the changed data source and the digital twin objects in the original data source belong to the same digital twin entity.

[0235] It should be noted here that the above first display module 1202 and second display module 1204 correspond to steps S902 to S904 in Embodiment 2. The instances and application scenarios implemented by the two modules and the corresponding steps are the same, but are not limited to the content disclosed in the above Embodiment 1. It should be noted that the above modules or units can be hardware components or software components stored in a memory (for example, memory 104) and processed by one or more processors (for example, processors 102a, 102b,..., 102n). The above modules can also be part of a device and can run in the computer terminal 10 provided in Embodiment 1.

[0236] It should be noted that the preferred implementation schemes involved in the above embodiments of the present application are the same as the schemes, application scenarios, and implementation processes provided in Embodiment 1, but are not limited to the schemes provided in Embodiment 1.

[0237] Embodiment 6

[0238] According to an embodiment of the present application, there is also provided a data processing device for a digital twin system for implementing the above data processing method of the digital twin system. Figure 13 It is a schematic diagram of a data processing device for a digital twin system according to an embodiment of the present application, as Figure 13 shown. The device 1300 includes: a call module 1302, a matching module 1304, a change module 1306, and an output module 1308.

[0239] Among them, the calling module is used to obtain the original data source and the changed data source of the digital twin system by calling the first interface in response to receiving a data processing instruction for the digital twin system. The first interface includes a first parameter, and the parameter value of the first parameter is the original data source and the changed data source. The matching module is used to match the digital twin objects in the changed data source with the digital twin objects in the original data source to obtain a matching result, where the matching result is used to indicate whether the digital twin objects in the changed data source and the digital twin objects in the original data source belong to the same digital twin entity. The change module is used to change the object attribute values of the digital twin objects in the original data source based on the change type of the changed data source and the matching result to obtain a first change result. The output module is used to output the first change result by calling the second interface. The second interface includes a second parameter, and the parameter value of the second parameter is the first change result.

[0240] It should be noted here that the above calling module 1302, matching module 1304, change module 1306, and output module 1308 correspond to steps S1002 to S1008 in Embodiment 3. The examples and application scenarios implemented by the four modules and the corresponding steps are the same, but are not limited to the content disclosed in the above Embodiment 1. It should be noted that the above modules or units can be hardware components or software components stored in a memory (for example, memory 104) and processed by one or more processors (for example, processors 102a, 102b,..., 102n). The above modules can also be part of a device and can run in the computer terminal 10 provided in Embodiment 1.

[0241] It should be noted that the preferred implementation schemes involved in the above embodiments of the present application are the same as the schemes, application scenarios, and implementation processes provided in Embodiment 1, but are not limited to the schemes provided in Embodiment 1.

[0242] Embodiment 7

[0243] An embodiment of the present application can provide a computer terminal, and the computer terminal can be any computer terminal device in a computer terminal group. Optionally, in this embodiment, the above computer terminal can also be replaced with a terminal device such as a mobile terminal.

[0244] Optionally, in this embodiment, the above computer terminal can be located in at least one of multiple network devices in a computer network.

[0245] In this embodiment, the above computer terminal may execute the program code of the following steps in the data processing method of the digital twin system: receiving a data processing instruction, and obtaining the original data source and the changed data source of the digital twin system; matching the digital twin objects in the changed data source with the digital twin objects in the original data source to obtain a matching result, where the matching result is used to indicate whether the digital twin objects in the changed data source and the digital twin objects in the original data source belong to the same digital twin entity; based on the change type of the changed data source and the matching result, changing the object attribute values of the digital twin objects in the original data source to obtain a first change result.

[0246] Optionally, Figure 14 is a structural block diagram of a computer terminal according to an embodiment of the present application. As Figure 14 shown, the computer terminal A may include: one or more (only one is shown in the figure) processors 102, a memory 104, a storage controller, and a peripheral interface, where the peripheral interface is connected to a radio frequency module, an audio module, and a display.

[0247] Among them, the memory can be used to store software programs and modules, such as the program instructions / modules corresponding to the data processing method and device of the digital twin system in the embodiment of the present application. The processor executes various functional applications and data processing by running the software programs and modules stored in the memory, that is, implements the data processing method of the above digital twin system. The memory may include a high-speed random access memory, and may also include a non-volatile memory, such as one or more magnetic storage devices, a flash memory, or other non-volatile solid-state memories. In some instances, the memory may further include a memory remotely provided with respect to the processor, and these remote memories may be connected to the terminal A through a network. Examples of the above network include but are not limited to the Internet, an enterprise intranet, a local area network, a mobile communication network, and combinations thereof.

[0248] The processor may call the information and application programs stored in the memory through a transmission device to execute the following steps: receiving a data processing instruction, and obtaining the original data source and the changed data source of the digital twin system; matching the digital twin objects in the changed data source with the digital twin objects in the original data source to obtain a matching result, where the matching result is used to indicate whether the digital twin objects in the changed data source and the digital twin objects in the original data source belong to the same digital twin entity; based on the change type of the changed data source and the matching result, changing the object attribute values of the digital twin objects in the original data source to obtain a first change result.

[0249] Optionally, the above-mentioned processor may also execute the program code of the following steps: If the matching result is that the digital twin object in the change data source and the digital twin object in the original data source belong to the same digital twin entity, the entity information record table in the original data source is changed based on the change type of the change data source and the first object attribute value of the digital twin object in the change data source to obtain a first change result, where the entity information record table is used to represent the information record table for the digital twin entity; If the matching result is that the digital twin object in the change data source and the digital twin object in the original data source correspond to different digital twin entities, the entity information record table is changed based on the change type of the change data source and the second object attribute value of the digital twin object and the digital twin object in the change data source to obtain a first change result.

[0250] Optionally, the above-mentioned processor may also execute the program code of the following steps: If the change type is the first change type, the current object attribute value of the digital twin object in the entity information record table is replaced based on the first object attribute value to obtain a first change result; If the change type is the second change type, the current object attribute value of the digital twin object in the entity information record table is replaced based on the time period granularity of the change data source and the first object attribute value to obtain a first change result, where the time period granularity is used to represent the division granularity of the total time period of the change data source, and the second change type and the first change type are used to distinguish change data sources with different change speeds.

[0251] Optionally, the above-mentioned processor may also execute the program code of the following steps: The total time period is divided based on the time period granularity to obtain multiple time windows; The sub-object attribute value is determined according to the first object attribute value and the multiple time windows; The current object attribute value of the digital twin object is replaced based on the sub-object attribute value to obtain a first change result.

[0252] Optionally, the above-mentioned processor may also execute the program code of the following steps: Determine whether the first object attribute value exists in the first time window among the multiple time windows, where the first time window is the last time window in the total time period; If the first object attribute value exists in the first time window, the sub-object attribute value corresponding to the first time window is determined according to the first object attribute value; If the first object attribute value does not exist in the first time window, the sub-object attribute value corresponding to the second time window is determined according to the first object attribute value, where the second time window is the time window adjacent to the first time window.

[0253] Optionally, the above-mentioned processor may also execute the program code of the following steps: processing the total time period using the initial neural network model to obtain the first time period granularity; dividing the total time period based on the first time period granularity to obtain multiple sample time windows; determining the coverage ratio of the target sample time window according to the first quantity of the multiple sample time windows and the second quantity of the target sample time window, where the target sample time window is the sample time window among the multiple sample time windows that contains the first object attribute value; constructing a loss function based on the coverage ratio and a preset coverage ratio; adjusting the model parameters of the initial neural network model using the loss function to obtain a target neural network model, where the target neural network model is used to process the total time period to obtain the time period granularity.

[0254] Optionally, the above-mentioned processor may also execute the program code of the following steps: updating the snapshot fact table of the digital twin system based on the first change result, where the snapshot fact table is used to represent the information record table for the digital twin object.

[0255] Optionally, the above-mentioned processor may also execute the program code of the following steps: receiving a page display instruction acting on the interaction interface, and displaying a target page on the interaction interface, where the target page is used to display at least one of the following: the current attribute information of the digital twin object, the attribute time series information of the digital twin object, the current attribute information is generated based on the entity information record table, and the attribute time series information is generated based on the snapshot fact table.

[0256] Optionally, the above-mentioned processor may also execute the program code of the following steps: receiving a selection instruction for the attribute time series information in the target page, and determining the historical attribute value of the digital twin object corresponding to the selection instruction in the attribute time series information; changing the entity information record table based on the historical attribute value to obtain a second change result.

[0257] Optionally, the above-mentioned processor may also execute the program code of the following steps: using a prediction model to predict the change time point of the digital twin system based on a preset time interval to obtain a target time series diagram, where the target time series diagram is used to represent the corresponding relationship between the predicted object attribute values predicted within the preset time interval and the change time points of the predicted object attribute values.

[0258] Optionally, the above-mentioned processor may also execute the program code of the following steps: obtaining the sample change time points and the sample object attribute values corresponding to the sample change time points in the target time interval of the snapshot fact table; determining the actual time series diagram of the target time interval based on the sample change time points and the sample object attribute values; using an initial prediction model to predict the sample change time points based on the target time interval to obtain a predicted time series diagram; adjusting the model parameters of the initial prediction model based on the predicted time series diagram and the actual time series diagram to obtain a prediction model.

[0259] The processor can call the information and application programs stored in the memory through the transmission device to execute the following steps: in response to an operation instruction acting on the operation interface, display the original data source and the changed data source of the digital twin system on the operation interface; in response to a processing instruction acting on the operation interface, display a first change result on the operation interface, where the first change result is obtained by changing the object attribute values of the digital twin objects in the original data source based on the change type of the changed data source and the matching result, and the matching result is obtained by matching the digital twin objects in the changed data source with the digital twin objects in the original data source, and the matching result is used to indicate whether the digital twin objects in the changed data source and the digital twin objects in the original data source belong to the same digital twin entity.

[0260] The processor can call the information and application programs stored in the memory through the transmission device to execute the following steps: in response to receiving a data processing instruction for the digital twin system, obtain the original data source and the changed data source of the digital twin system by calling a first interface, where the first interface includes a first parameter, and the parameter value of the first parameter is the original data source and the changed data source; match the digital twin objects in the changed data source with the digital twin objects in the original data source to obtain a matching result, where the matching result is used to indicate whether the digital twin objects in the changed data source and the digital twin objects in the original data source belong to the same digital twin entity; change the object attribute values of the digital twin objects in the original data source based on the change type of the changed data source and the matching result to obtain a first change result; output the first change result by calling a second interface, where the second interface includes a second parameter, and the parameter value of the second parameter is the first change result.

[0261] By adopting the embodiment of the present application, first, a data processing instruction is received, and the original data source and the changed data source of the digital twin system are obtained; the digital twin objects in the changed data source are matched with the digital twin objects in the original data source to obtain a matching result, where the matching result is used to indicate whether the digital twin objects in the changed data source and the digital twin objects in the original data source belong to the same digital twin entity; the object attribute values of the digital twin objects in the original data source are changed based on the change type of the changed data source and the matching result to obtain a first change result, which improves the management efficiency of attribute changes in the digital twin system. It is easy to notice that matching can be performed on different types of digital twin objects in the received changed data source, so as to change the object attribute values of the digital twin objects in the original data source according to the object attribute values of the digital twin objects in the changed data source, so that the attribute changes of the digital twin objects are consistent, and the digital twin objects can display the same object attribute values among different users. Through the matching method, the object attribute values corresponding to the digital twin objects can be updated, thereby improving the management efficiency of attribute changes, and further solving the technical problem of poor management efficiency of attribute changes in the digital twin system in the related art.

[0262] Those of ordinary skill in the art can understand that Figure 14 the structure shown is only for illustration, and the computer terminal can also be a smart phone (such as an Android phone, an iOS phone, etc.), a tablet computer, a handheld computer, and a mobile Internet device (Mobile Internet Devices, MID), a PAD and other terminal devices. Figure 14 It does not limit the structure of the above electronic device. For example, the computer terminal A may further include more or fewer components (such as a network interface, a display device, etc.) than those shown Figure 14 in the figure, or have a different configuration from that shown Figure 14 in the figure.

[0263] Those of ordinary skill in the art can understand that all or part of the steps in the various methods of the above embodiments can be completed by instructing the relevant hardware of the terminal device through a program, and the program can be stored in a computer-readable storage medium. The storage medium may include: a flash drive, a read-only memory (Read-Only Memory, ROM), a random access memory (Random Access Memory, RAM), a magnetic disk or an optical disc, etc.

[0264] Embodiment 4

[0265] The embodiment of the present application further provides a storage medium. Optionally, in this embodiment, the above storage medium can be used to save the program code executed by the data processing method of the digital twin system provided in the first embodiment above.

[0266] Optionally, in this embodiment, the above storage medium may be located in any one of the computer terminals in the computer terminal group in the computer network, or in any one of the mobile terminals in the mobile terminal group.

[0267] Optionally, in this embodiment, the storage medium is configured to store program code for performing the following steps: receiving a data processing instruction, and obtaining the original data source and the changed data source of the digital twin system; matching the digital twin objects in the changed data source with the digital twin objects in the original data source to obtain a matching result, where the matching result is used to indicate whether the digital twin objects in the changed data source and the digital twin objects in the original data source belong to the same digital twin entity; and changing the object attribute values of the digital twin objects in the original data source based on the change type of the changed data source and the matching result to obtain a first change result.

[0268] Optionally, the above processor may further execute program code for performing the following steps: if the matching result is that the digital twin objects in the changed data source and the digital twin objects in the original data source belong to the same digital twin entity, changing the entity information record table in the original data source based on the change type of the changed data source and the first object attribute value of the digital twin objects in the changed data source to obtain a first change result, where the entity information record table is used to represent the information record table for the digital twin entity; if the matching result is that the digital twin objects in the changed data source and the digital twin objects in the original data source correspond to different digital twin entities, changing the entity information record table based on the change type of the changed data source and the second object attribute value of the digital twin objects and the digital twin objects in the changed data source to obtain a first change result.

[0269] Optionally, the above processor may further execute program code for performing the following steps: if the change type is the first change type, replacing the current object attribute value of the digital twin object in the entity information record table based on the first object attribute value to obtain a first change result; if the change type is the second change type, replacing the current object attribute value of the digital twin object in the entity information record table based on the time period granularity of the changed data source and the first object attribute value to obtain a first change result, where the time period granularity is used to represent the division granularity of the total time period of the changed data source, and the second change type and the first change type are used to distinguish the changed data sources with different change speeds.

[0270] Optionally, the above processor may further execute program code for performing the following steps: dividing the total time period based on the time period granularity to obtain a plurality of time windows; determining sub-object attribute values according to the first object attribute value and the plurality of time windows; and replacing the current object attribute value of the digital twin object based on the sub-object attribute values to obtain a first change result.

[0271] Optionally, the above-mentioned processor may also execute the program code of the following steps: determine whether a first object attribute value exists in a first time window among multiple time windows, where the first time window is the last time window in the total time period; if the first object attribute value exists in the first time window, determine a sub-object attribute value corresponding to the first time window according to the first object attribute value; if the first object attribute value does not exist in the first time window, determine a sub-object attribute value corresponding to a second time window according to the first object attribute value, where the second time window is a time window adjacent to the first time window.

[0272] Optionally, the above-mentioned processor may also execute the program code of the following steps: process the total time period using an initial neural network model to obtain a first time period granularity; divide the total time period based on the first time period granularity to obtain multiple sample time windows; determine a coverage ratio of a target sample time window according to a first quantity of the multiple sample time windows and a second quantity of the target sample time window, where the target sample time window is a sample time window among the multiple sample time windows that contains the first object attribute value; construct a loss function based on the coverage ratio and a preset coverage ratio; adjust model parameters of the initial neural network model using the loss function to obtain a target neural network model, where the target neural network model is used to process the total time period to obtain a time period granularity.

[0273] Optionally, the above-mentioned processor may also execute the program code of the following steps: update a snapshot fact table of the digital twin system based on a first change result, where the snapshot fact table is used to represent an information record table for digital twin objects.

[0274] Optionally, the above-mentioned processor may also execute the program code of the following steps: receive a page display instruction acting on an interaction interface, and display a target page on the interaction interface, where the target page is used to display at least one of the following: current attribute information of a digital twin object, attribute time series information of the digital twin object, the current attribute information is generated based on an entity information record table, and the attribute time series information is generated based on the snapshot fact table.

[0275] Optionally, the above-mentioned processor may also execute the program code of the following steps: receive a selection instruction for the attribute time series information in the target page, and determine a historical attribute value of the digital twin object corresponding to the selection instruction in the attribute time series information; change the entity information record table based on the historical attribute value to obtain a second change result.

[0276] Optionally, the above-mentioned processor may also execute the program code of the following steps: Use a prediction model to predict the change time points of the digital twin system based on a preset time interval to obtain a target time series diagram, where the target time series diagram is used to represent the correspondence between the predicted object attribute values and the change time points of the predicted object attribute values within the preset time interval.

[0277] Optionally, the above-mentioned processor may also execute the program code of the following steps: Obtain the sample change time points and the corresponding sample object attribute values of the target time interval in the snapshot fact table; Determine the actual time series diagram of the target time interval based on the sample change time points and the sample object attribute values; Use an initial prediction model to predict the sample change time points based on the target time interval to obtain a predicted time series diagram; Adjust the model parameters of the initial prediction model based on the predicted time series diagram and the actual time series diagram to obtain a prediction model.

[0278] The processor may call the information and application programs stored in the memory through the transmission device to execute the following steps: Respond to the operation instruction acting on the operation interface, and display the original data source and the change data source of the digital twin system on the operation interface; Respond to the processing instruction acting on the operation interface, and display the first change result on the operation interface, where the first change result is obtained by changing the object attribute values of the digital twin objects in the original data source based on the change type of the change data source and the matching result, and the matching result is obtained by matching the digital twin objects in the change data source with the digital twin objects in the original data source, and the matching result is used to indicate whether the digital twin objects in the change data source and the digital twin objects in the original data source belong to the same digital twin entity.

[0279] The processor may call the information and application programs stored in the memory through the transmission device to execute the following steps: Respond to receiving the data processing instruction for the digital twin system, and obtain the original data source and the change data source of the digital twin system by calling the first interface, where the first interface includes a first parameter, and the parameter value of the first parameter is the original data source and the change data source; Match the digital twin objects in the change data source with the digital twin objects in the original data source to obtain a matching result, where the matching result is used to indicate whether the digital twin objects in the change data source and the digital twin objects in the original data source belong to the same digital twin entity; Change the object attribute values of the digital twin objects in the original data source based on the change type of the change data source and the matching result to obtain a first change result; Output the first change result by calling the second interface, where the second interface includes a second parameter, and the parameter value of the second parameter is the first change result.

[0280] Using the embodiments of the present application, first, a data processing instruction is received, and the original data source and the changed data source of the digital twin system are obtained; the digital twin objects in the changed data source are matched with the digital twin objects in the original data source to obtain a matching result, where the matching result is used to indicate whether the digital twin objects in the changed data source and the digital twin objects in the original data source belong to the same digital twin entity; the object attribute values of the digital twin objects in the original data source are changed based on the change type of the changed data source and the matching result to obtain a first change result, which improves the management efficiency of attribute changes in the digital twin system. It is easy to notice that matching can be performed on different types of digital twin objects in the received changed data source, so as to change the object attribute values of the digital twin objects in the original data source according to the object attribute values of the digital twin objects in the changed data source, so that the attribute changes of the digital twin objects are consistent, enabling the digital twin objects to display the same object attribute values among different users. Through the matching method, the object attribute values corresponding to the digital twin objects can be updated, thereby improving the management efficiency of attribute changes, and further solving the technical problem of poor management efficiency of attribute changes in the digital twin system in the related art.

[0281] The serial numbers of the above embodiments of the present application are only for description and do not represent the advantages or disadvantages of the embodiments.

[0282] In the above embodiments of the present application, the descriptions of the various embodiments have their own emphases. For the parts not detailed in a certain embodiment, reference may be made to the relevant descriptions of other embodiments.

[0283] In the several embodiments provided by the present application, it should be understood that the disclosed technical content can be implemented in other ways. Among them, the device embodiments described above are only illustrative. For example, the division of the units is only a logical function division. In actual implementation, there may be other division methods. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed mutual coupling or direct coupling or communication connection can be through some interfaces. The indirect coupling or communication connection of units or modules can be in an electrical or other form.

[0284] The units described as separate components may or may not be physically separated. The components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0285] In addition, in each embodiment of the present application, each functional unit can be integrated into a processing unit, or each unit can exist physically alone, or two or more units can be integrated into one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of a software functional unit.

[0286] If the above-mentioned integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on such an understanding, the technical solution of the present application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in each embodiment of the present application. The foregoing storage medium includes: various media such as USB flash drives, read-only memories (ROMs), random access memories (RAMs), mobile hard disks, magnetic disks, or optical discs that can store program codes.

[0287] The above are only the preferred embodiments of the present application. It should be noted that for those of ordinary skill in the art, without departing from the principle of the present application, several improvements and refinements can be made, and these improvements and refinements should also be regarded as the protection scope of the present application.

Claims

1. A data processing method for a digital twin system, characterized in that, The digital twin system is used to manage digital twin entities in the real world through digital twin objects in the virtual world. The method includes: Receiving a data processing instruction, and obtaining the original data source and the changed data source of the digital twin system; Matching the digital twin objects in the changed data source with the digital twin objects in the original data source to obtain a matching result, where the matching result is used to indicate whether the digital twin objects in the changed data source and the digital twin objects in the original data source belong to the same digital twin entity; Changing the object attribute values of the digital twin objects in the original data source based on the change type of the changed data source and the matching result to obtain a first change result.

2. The data processing method of the digital twin system according to claim 1, characterized in that, Changing the object attribute values of the digital twin objects in the original data source based on the change type of the changed data source and the matching result to obtain a first change result, including: If the matching result is that the digital twin objects in the changed data source and the digital twin objects in the original data source belong to the same digital twin entity, changing the entity information record table in the original data source based on the change type of the changed data source and the first object attribute value of the digital twin objects in the changed data source to obtain the first change result, where the entity information record table is used to represent the information record table for the digital twin entity; If the matching result is that the digital twin objects in the changed data source and the digital twin objects in the original data source correspond to different digital twin entities, changing the entity information record table based on the change type of the changed data source and the second object attribute value of the digital twin objects and the digital twin objects in the changed data source to obtain the first change result.

3. The data processing method of the digital twin system according to claim 2, characterized in that Changing the entity information record table in the original data source based on the change type of the changed data source and the first object attribute value of the digital twin objects in the changed data source to obtain the first change result, including: If the change type is the first change type, replacing the current object attribute value of the digital twin object in the entity information record table based on the first object attribute value to obtain the first change result; If the change type is the second change type, replacing the current object attribute value of the digital twin object in the entity information record table based on the time period granularity of the changed data source and the first object attribute value to obtain the first change result, where the time period granularity is used to represent the division granularity of the total time period of the changed data source, and the second change type and the first change type are used to distinguish the changed data sources with different change speeds.

4. The data processing method of the digital twin system according to claim 3, characterized in that, Replacing the current object attribute value of the digital twin object in the entity information record table based on the time period granularity of the changed data source and the first object attribute value to obtain the first change result, including: Divide the total time period based on the time period granularity to obtain a plurality of time windows; Determine sub-object attribute values according to the first object attribute value and the plurality of time windows; Replace the current object attribute value of the digital twin object based on the sub-object attribute value to obtain the first change result.

5. The data processing method of the digital twin system according to claim 4, characterized in that Determining sub-object attribute values according to the first object attribute value and the plurality of time windows includes: Determine whether the first object attribute value exists in the first time window among the plurality of time windows, where the first time window is the last time window in the total time period; If the first object attribute value exists in the first time window, determine the sub-object attribute value corresponding to the first time window according to the first object attribute value; If the first object attribute value does not exist in the first time window, determine the sub-object attribute value corresponding to the second time window according to the first object attribute value, where the second time window is the time window adjacent to the first time window.

6. The data processing method of the digital twin system according to claim 5, wherein The method further includes: Process the total time period using an initial neural network model to obtain a first time period granularity; Divide the total time period based on the first time period granularity to obtain a plurality of sample time windows; Determine the coverage ratio of the target sample time window according to the first quantity of the plurality of sample time windows and the second quantity of the target sample time window, where the target sample time window is the sample time window among the plurality of sample time windows that contains the first object attribute value; Construct a loss function based on the coverage ratio and a preset coverage ratio; Adjust the model parameters of the initial neural network model using the loss function to obtain a target neural network model, where the target neural network model is used to process the total time period to obtain the time period granularity.

7. The data processing method of the digital twin system according to claim 2, characterized in that The method further includes: Update the snapshot fact table of the digital twin system based on the first change result, where the snapshot fact table is used to represent the information record table for the digital twin object.

8. The data processing method of the digital twin system according to claim 7, characterized in that The method further includes: Upon receiving a page display instruction acting on the interaction interface, display a target page on the interaction interface, where the target page is used to display at least one of the following: the current attribute information of the digital twin object, the attribute time series information of the digital twin object, the current attribute information is generated based on the entity information record table, and the attribute time series information is generated based on the snapshot fact table.

9. The data processing method of the digital twin system according to claim 8, wherein The method further includes: Upon receiving a selection instruction for the attribute time series information in the target page, determine the historical attribute value of the digital twin object corresponding to the selection instruction in the attribute time series information; Modify the entity information record table based on the historical attribute value to obtain a second change result.

10. The data processing method of the digital twin system according to claim 9, wherein The method further includes: Using a prediction model to predict the change time points of the digital twin system based on a preset time interval, obtaining a target time series graph, where the target time series graph is used to represent the correspondence between the predicted attribute values of the prediction object and the change time points of the predicted attribute values of the prediction object within the preset time interval.

11. The data processing method of the digital twin system according to claim 10, characterized in that The method further includes: Obtaining the sample change time points in the target time interval in the snapshot fact table and the sample object attribute values corresponding to the sample change time points; Determining the actual time series graph of the target time interval based on the sample change time points and the sample object attribute values; Using an initial prediction model to predict the sample change time points based on the target time interval, obtaining a predicted time series graph; Adjusting the model parameters of the initial prediction model based on the predicted time series graph and the actual time series graph to obtain the prediction model.

12. A data processing method for a digital twin system, characterized in that, The digital twin system is used to manage the digital twin entities in the real world through the digital twin objects in the virtual world. The method includes: Responding to an operation instruction acting on the operation interface, and displaying the original data source and the change data source of the digital twin system on the operation interface; Responding to a processing instruction acting on the operation interface, and displaying a first change result on the operation interface, where the first change result is obtained by changing the object attribute values of the digital twin objects in the original data source based on the change type and the matching result of the change data source, and the matching result is obtained by matching the digital twin objects in the change data source with the digital twin objects in the original data source, where the matching result is used to represent whether the digital twin objects in the change data source and the digital twin objects in the original data source belong to the same digital twin entity.

13. A data processing method for a digital twin system, characterized in that, The digital twin system is used to manage the digital twin entities in the real world through the digital twin objects in the virtual world, including: Responding to receiving a data processing instruction for the digital twin system, obtaining the original data source and the change data source of the digital twin system by calling a first interface, where the first interface includes a first parameter, and the parameter value of the first parameter is the original data source and the change data source; Matching the digital twin objects in the change data source with the digital twin objects in the original data source to obtain a matching result, where the matching result is used to represent whether the digital twin objects in the change data source and the digital twin objects in the original data source belong to the same digital twin entity; Changing the object attribute values of the digital twin objects in the original data source based on the change type of the change data source and the matching result to obtain a first change result; Outputting the first change result by calling a second interface, where the second interface includes a second parameter, and the parameter value of the second parameter is the first change result.

14. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes a stored executable program, wherein when the executable program runs, it controls the device where the computer-readable storage medium is located to execute the data processing method of the digital twin system according to any one of claims 1 to 13.

15. An electronic device, characterized in that, Comprising: a memory storing an executable program; a processor for running the program, wherein when the program runs, it executes the data processing method of the digital twin system according to any one of claims 1 to 13.

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