Intelligent complex system construction methods, devices, equipment, media and products

Abstract

The present application relates to a method, device, equipment, medium and product for constructing an intelligent complex system. The method comprises: in response to a construction request of a target intelligent complex system, according to a system requirement document, determining multiple modeling attributes of the target intelligent complex system and attribute description information of each modeling attribute; the attribute description information comprises multiple subtasks of at least one system task, capability information required for each subtask and system support resources; according to each modeling attribute and each attribute description information, determining the intelligent system architecture of the target intelligent complex system; and constructing the target intelligent complex system based on the intelligent system architecture. The method can effectively construct an intelligent complex system.

Description

Technical Field

[0001] The present application relates to the fields of information technology and communication technology, and in particular to a method, device, equipment, medium and product for constructing an intelligent complex system. Background Art

[0002] An intelligent complex system refers to a system that is formed by the dynamic combination of a series of intelligent systems. For example, smart cities, smart parks, and smart factories can all be considered as special intelligent complex systems.

[0003] The establishment of intelligent complex systems helps solve problems such as environmental pollution, energy waste, and irrational resource allocation, thereby reducing pollution, saving energy, and improving resource utilization. In the face of the rapid rise of intelligent business in the future and the urgent need for systematic construction of smart cities, smart parks, and smart factories, it is crucial to correctly understand user needs and build intelligent complex systems.

[0004] Therefore, how to build an intelligent complex system is a problem that needs to be solved urgently. Summary of the invention

[0005] Based on this, it is necessary to provide a method, device, equipment, medium and product for constructing an intelligent complex system to address the above-mentioned technical problems, so as to effectively construct an intelligent complex system.

[0006] In a first aspect, the present application provides a method for constructing an intelligent complex system, comprising:

[0007] In response to a request to build a target intelligent complex system, multiple modeling attributes of the target intelligent complex system and attribute description information of each modeling attribute are determined according to a system requirement document; the attribute description information includes multiple subtasks of at least one system task, capability information required for each subtask, and system support resources;

[0008] Determine the intelligent system architecture of the target intelligent complex system based on each modeling attribute and each attribute description information;

[0009] Build the target intelligent complex system based on the intelligent system architecture.

[0010] In one embodiment, according to the system requirement document, multiple modeling attributes of the target intelligent complex system and attribute description information of each modeling attribute are determined, including:

[0011] According to multiple layers in the preset intelligent system architecture framework information, multiple layer attributes in each layer and attribute description rules of each layer attribute are obtained;

[0012] Determine each modeling attribute based on the system requirements document and the attributes of each layer;

[0013] Based on the attribute description rules of each modeling attribute and each layer attribute, attribute description information of each modeling attribute is determined.

[0014] In one embodiment, the modeling attributes are determined according to the system requirement document and the attributes of each layer, including:

[0015] According to the system requirements document, obtain the implementation functions, application fields and application modes of the target intelligent complex system;

[0016] According to the implemented functions, application fields and application modes, the business requirement decomposition attributes, capability classification attributes and essential resource attributes in each layer attribute are determined as various modeling attributes.

[0017] In one embodiment, each modeling attribute includes a business requirement decomposition attribute, a capability classification attribute, and a required resource attribute; based on the attribute description rules of each modeling attribute and each layer attribute, the attribute description information of each modeling attribute is determined, including:

[0018] According to the attribute description rules of each layer attribute, the attribute description rules of the business requirement decomposition attribute, the attribute description rules of the capability classification attribute and the attribute description rules of the required resource attribute are obtained;

[0019] Determine the attribute description information of the business requirement decomposition attributes according to the system requirement document and the attribute description rules of the business requirement decomposition attributes;

[0020] Determine attribute description information of the capability classification attribute according to the attribute description rule of the capability classification attribute;

[0021] According to the attribute description rule of the essential resource attribute, the attribute description information of the essential resource attribute is determined.

[0022] In one embodiment, determining the attribute description information of the business requirement decomposition attribute according to the system requirement document and the attribute description rule of the business requirement decomposition attribute includes:

[0023] Decompose the system tasks of the target intelligent complex system in the system requirement document to obtain multiple subtasks of the target intelligent complex system;

[0024] Describe each subtask according to the attribute description rules of the business requirement decomposition attributes to obtain subtask description information;

[0025] The subtask description information is used as the attribute description information of the business requirement decomposition attribute.

[0026] In one embodiment, determining the attribute description information of the capability classification attribute according to the attribute description rule of the capability classification attribute includes:

[0027] According to the task capability knowledge base and multiple subtasks of the target intelligent complex system, the system capability of the target intelligent complex system is decomposed to obtain multiple sub-capabilities of the target intelligent complex system;

[0028] Describe each sub-capability according to the attribute description rule of the capability classification attribute to obtain sub-capability description information;

[0029] The sub-capability description information is used as the attribute description information of the capability classification attribute.

[0030] In one embodiment, determining the attribute description information of the essential resource attribute according to the attribute description rule of the essential resource attribute includes:

[0031] Determine the system support resources of the target intelligent complex system based on the capability resource knowledge base and multiple sub-capabilities of the target intelligent complex system;

[0032] Describe the system support resources according to the attribute description rules of the necessary resource attributes to obtain resource description information;

[0033] The resource description information is determined as the attribute description information of the required resource attributes.

[0034] In one embodiment, determining the intelligent system architecture of the target intelligent complex system according to each modeling attribute and each attribute description information includes:

[0035] Determine the initial intelligent system architecture of the target intelligent complex system based on each modeling attribute and each attribute description information;

[0036] The initial intelligent system architecture is verified to obtain the intelligent system architecture.

[0037] In one embodiment, the initial intelligent system architecture is verified to obtain the intelligent system architecture, including:

[0038] Verify the data completeness of the initial intelligent system architecture and obtain the candidate intelligent system architecture;

[0039] According to each modeling attribute and each attribute description information, the candidate intelligent system architecture is verified for data consistency to obtain the intelligent system architecture.

[0040] In one embodiment, data completeness verification is performed on the initial intelligent system architecture to obtain a candidate intelligent system architecture, including:

[0041] Model and simulate the initial intelligent system architecture to obtain a virtual intelligent complex system corresponding to the initial intelligent system architecture;

[0042] Run virtual intelligent complex systems;

[0043] If the virtual intelligent complex system operates normally, the initial intelligent system architecture is determined as the candidate intelligent system architecture.

[0044] In one embodiment, the method further comprises:

[0045] If the virtual intelligent complex system operates abnormally, the virtual intelligent complex system is adjusted;

[0046] Obtaining the initial intelligent system architecture after synchronization adjustment with the virtual intelligent complex system;

[0047] The adjusted initial intelligent system architecture is determined as a candidate intelligent system architecture.

[0048] In one embodiment, data consistency verification is performed on the candidate intelligent system architecture according to each modeling attribute and each attribute description information to obtain the intelligent system architecture, including:

[0049] According to the description information of each attribute, the data consistency check is performed on the modeling attributes in the same layer and the modeling attributes associated between different layers;

[0050] If the key information in the modeling attributes in the same layer is consistent, and the key information of the modeling attributes associated between different layers is consistent, then the candidate intelligent architecture is determined to be the intelligent architecture;

[0051] If there is inconsistent information between the key information of the modeling attributes in the same layer and the key information of the modeling attributes associated between different layers, the description information of each attribute is adjusted, and the intelligent system architecture is determined based on the adjusted attribute description information.

[0052] In one embodiment, a target intelligent complex system is constructed based on an intelligent system architecture, including:

[0053] Obtaining system construction data corresponding to each attribute description information;

[0054] Fill the system construction data into the corresponding position of the intelligent system architecture to obtain the target intelligent complex system.

[0055] In a second aspect, the present application also provides an intelligent complex system construction device, comprising:

[0056] An attribute information determination module is used to respond to a construction request of a target intelligent complex system and determine multiple modeling attributes of the target intelligent complex system and attribute description information of each modeling attribute according to a system requirement document; the attribute description information includes multiple subtasks of at least one system task, capability information required for each subtask, and system support resources;

[0057] The system architecture determination module is used to determine the intelligent system architecture of the target intelligent complex system according to each modeling attribute and each attribute description information;

[0058] Intelligent system building module, used to build the target intelligent complex system based on the intelligent system architecture.

[0059] In a third aspect, the present application also provides a computer device, which includes a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps in any one of the embodiments of the first aspect when executing the computer program.

[0060] In a fourth aspect, the embodiments of the present application further provide a computer-readable storage medium, wherein a computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, the steps in any one of the embodiments of the first aspect are implemented.

[0061] In a fifth aspect, the embodiments of the present application further provide a computer program product, which includes a computer program, and when the computer program is executed by a processor, the steps in any one of the embodiments in the first aspect are implemented.

[0062] The above-mentioned intelligent complex system construction method, device, equipment, medium and product, by responding to the construction request of the target intelligent complex system, determine multiple modeling attributes of the target intelligent complex system and attribute description information of each modeling attribute according to the system requirements document, and then determine the intelligent system architecture of the target intelligent complex system according to each modeling attribute and each attribute description information, and then build the target intelligent complex system based on the intelligent system architecture, wherein the attribute description information includes multiple subtasks of at least one system task, capability information required for each subtask and system support resources. In this method, when it is necessary to build the target intelligent complex system, starting from user needs, according to the system requirements document, the modeling attributes of the target intelligent complex system and the attribute description information of each modeling attribute are determined, so that the tasks to be completed, the capabilities and the supporting resources to be possessed when building the target intelligent complex system are clarified, and then a basic structural framework, namely the intelligent system architecture, is initially obtained according to each modeling attribute and each attribute description information. Based on the intelligent system architecture, the target intelligent complex system can be quickly constructed, which provides a unified standard specification for building an intelligent complex system and improves the level of flexible adaptation of the intelligent complex system to the needs of intelligent business. BRIEF DESCRIPTION OF THE DRAWINGS

[0063] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the related technologies, the drawings required for use in the embodiments or the related technical descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0064] Figure 1 is an internal structure diagram of a computer device in one embodiment;

[0065] Figure 2 A schematic diagram of a process of constructing a smart complex system in one embodiment;

[0066] Figure 3 A schematic diagram of a process for determining modeling attributes and attribute description information in one embodiment;

[0067] Figure 4 A diagram showing the relationship between all layers of an intelligent system architecture framework in one embodiment;

[0068] Figure 5 A schematic diagram of the relationship between the top-level design layer attributes in one embodiment;

[0069] Figure 6 is a schematic diagram of the relationship between attributes of the business capability layer in one embodiment;

[0070] Figure 7 A schematic diagram of the relationship between attributes of the business logic layer in one embodiment;

[0071] Figure 8 A schematic diagram of the relationship between system resource layer attributes in one embodiment;

[0072] Fig. 9 is a schematic diagram of the relationship between the attributes of the intelligent technology layer in one embodiment;

[0073] Fig.10 A schematic diagram of the relationship between attributes of the human factors layer of a system in one embodiment;

[0074] Fig.11 A schematic diagram of the relationship between attributes of the business rule layer in one embodiment;

[0075] Fig.12 is a schematic diagram of the relationship between standard specifications and evaluation layer attributes in one embodiment;

[0076] Fig.13 A diagram showing the relationship between the top-level design layer and the properties of other layers in one embodiment;

[0077] Fig.14 A diagram showing the relationship between other layer attributes and the top-level design layer in one embodiment;

[0078] Fig.15 A diagram showing the relationship between the business capability layer and other layer attributes in an embodiment;

[0079] Fig.16 A diagram showing the relationship between other layer attributes and the business capability layer in an embodiment;

[0080] Fig.17 A diagram showing the relationship between the business logic layer and other layer attributes in an embodiment;

[0081] Fig.18 A diagram showing the relationship between other layer attributes and the business logic layer in one embodiment;

[0082] Fig.19 A diagram showing the relationship between the system resource layer and other layer attributes in an embodiment;

[0083] Fig. 20 A diagram showing the relationship between other layer attributes and the system resource layer in an embodiment;

[0084] FIG21 is a diagram showing the relationship between the intelligent technology layer and other layer attributes in one embodiment;

[0085] FIG22 is a diagram showing the relationship between other layer attributes and the intelligent technology layer in one embodiment;

[0086] FIG23 is a diagram showing the relationship between the human factor layer of the system and the attributes of other layers in one embodiment;

[0087] FIG24 is a diagram showing the relationship between other layer attributes and the human factors layer of the system in one embodiment;

[0088] FIG25 is a diagram showing the relationship between the business rule layer and other layer attributes in one embodiment;

[0089] FIG26 is a diagram showing the relationship between other layer attributes and the business rule layer in one embodiment;

[0090] FIG27 is a diagram showing the relationship between the standard specification and the evaluation layer and the properties of other layers in one embodiment;

[0091] FIG28 is a diagram showing the relationship between other layer attributes and the standard specification and evaluation layer in one embodiment;

[0092] FIG29 is a schematic diagram of a process for determining attribute description information in one embodiment;

[0093] FIG30 is a schematic diagram of attribute description information of a business requirement decomposition attribute in one embodiment;

[0094] FIG31 is a schematic diagram of attribute description information of a component system classification attribute in one embodiment;

[0095] FIG32 is a schematic diagram of a process for determining an intelligent system architecture in one embodiment;

[0096] FIG33 is a schematic diagram of a flow chart of a method for constructing an intelligent complex system in another embodiment;

[0097] FIG34 is a schematic diagram of the structure of an intelligent complex system building device in one embodiment. DETAILED DESCRIPTION

[0098] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0099] The intelligent complex system construction method provided in the embodiment of the present application can be applied to a computer device. The computer device can be a server, and its internal structure diagram can be as follows: Figure 1 As shown. The computer device includes a processor, a memory, an input / output interface (Input / Output, referred to as I / O) and a communication interface. The processor, memory and input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage medium. The database of the computer device is used to store data. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a method for constructing an intelligent complex system is implemented. Those skilled in the art can understand that Figure 1 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0100] With the rapid development of technologies such as the Internet, big data, and artificial intelligence, previously isolated systems have been closely interconnected, and a series of intelligent systems have been dynamically combined to form an intelligent complex system. Research on intelligent complex systems can help solve problems such as environmental pollution, energy waste, and irrational resource allocation in existing systems, thereby reducing pollution, saving energy, and improving resource utilization. Smart cities, smart parks, and smart factories can all be regarded as special intelligent complex systems.

[0101] In the face of the rapid rise of intelligent business in the future, as well as the urgent need for systematic construction of smart cities, smart parks, smart factories, etc., especially in the context of the rapid development of the field of intelligent complex systems, it is crucial to correctly understand user needs and design intelligent complex systems. Forward design capabilities are essential. Forward design capabilities refer to starting from user needs, clarifying top-level design requirements, decomposing and refining the functions and performance of intelligent complex systems from top to bottom, clarifying the solutions for the functional structure of intelligent complex systems, component system interactions, etc., in order to form the ability to support the design, construction, application and management of intelligent complex systems throughout their life cycle. Through forward design, user needs are decomposed from top to bottom to build a spectrum of technologies, resources, and capabilities for intelligent complex systems under typical tasks, meet heterogeneous user needs, and provide a key driving force for users to move from imitation to independent innovation.

[0102] Intelligent complex systems have shown broad application prospects since their inception, but they often face a series of challenges in the actual implementation process. The most notable one is that their theoretical ideas lack concrete and operational implementation methods, which makes the implementation process extremely difficult. At the same time, the lack of effective top-level guidance in the implementation process is also a major obstacle.

[0103] Based on this, the present application provides a method for constructing an intelligent complex system. When it is necessary to construct a target intelligent complex system, starting from user needs, according to the system requirements document, the modeling attributes for constructing the target intelligent complex system and the attribute description information of each modeling attribute are determined. In this way, the tasks to be completed, the capabilities to be possessed, and the supporting resources to be completed when constructing the target intelligent complex system are clarified, and then a basic structural framework, namely, the intelligent system architecture, is preliminarily obtained based on each modeling attribute and each attribute description information. Based on the intelligent system architecture, the target intelligent complex system can be quickly constructed, which provides a unified standard specification for constructing an intelligent complex system and improves the level of flexible adaptation of the intelligent complex system to the needs of intelligent business.

[0104] It should be noted that the beneficial effects brought about by the embodiments of the present application or the technical problems solved are not limited to this one, but may also include other implicit or related problems. For details, please refer to the description of the following embodiments.

[0105] The technical solution of the present application and how the technical solution of the present application solves the above-mentioned technical problems are described in detail below with specific embodiments. The following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments. The embodiments of the present application will be described below in conjunction with the accompanying drawings.

[0106] In an exemplary embodiment, Figure 2 As shown in the figure, a method for constructing an intelligent complex system is provided, which can be applied to Figure 1 The computer device in the example is used to illustrate, including the following steps 201 to 203. Among them:

[0107] S201, in response to a request to build a target intelligent complex system, determine multiple modeling attributes of the target intelligent complex system and attribute description information of each modeling attribute according to the system requirement document; the attribute description information includes multiple subtasks of at least one system task, capability information required for each subtask, and system support resources.

[0108] The construction request of the target intelligent complex system refers to a request triggered when the target intelligent complex system needs to be constructed in the system construction application of the computer device. Naturally, after receiving the construction request, the computer device needs to construct the target intelligent complex system.

[0109] The request can be triggered by the target user through a computer device in the system construction application; wherein, the triggering method includes but is not limited to external input device click, voice control, touch screen trigger, etc., and the embodiment of the present application does not limit the triggering method.

[0110] In the embodiments of the present application, the system requirements document refers to a document that defines the mission, scope of use, and overall goals of the system. In one embodiment, through in-depth cooperation and communication with multiple stakeholders, the expectations and needs of all parties can be fully understood, including the end users, business owners, etc. of the target intelligent complex system, to generate a clear and measurable system requirements document. Among them, the system requirements document needs to describe in detail the functions, fields, and application scenarios of the target intelligent complex system to ensure that all relevant parties have a clear understanding of the system and provide strong guidance for subsequent development work.

[0111] Modeling attributes refer to various features or properties used to describe the target intelligent complex system. For example, modeling attributes may include, but are not limited to, system planning attributes, summary information attributes, comprehensive dictionary attributes, capability requirements attributes, capability vision attributes, capability classification attributes, capability baseline attributes, capability dependency attributes, capability and task mapping attributes, business concept map attributes, business requirement decomposition attributes, task and rule association attributes, task and organization mapping attributes, capability and component system mapping attributes, resource and business capability attributes, required resource attributes, technology classification attributes, etc.

[0112] The attribute description information of the modeling attribute refers to the information obtained by summarizing and analyzing the properties and relationships of the target intelligent complex system. For example, if the modeling attribute is a business concept map attribute, the attribute description information of the business concept map attribute is to describe what the intelligent complex system should do and how to do it.

[0113] System tasks refer to the tasks to be completed when facing the construction of a target intelligent complex system. For example, a company faces the following problem: In Park A, there are systems such as energy, logistics, security, environmental protection, and geographic information. At present, these systems are not related to each other and cannot maximize the effectiveness of the system. At the same time, the current park system has problems such as environmental pollution, energy waste, and unreasonable resource coordination, and it is urgent to build an interconnected smart park system. At this time, the system task can be to build an interconnected smart park system for Park A. Subtasks refer to small tasks obtained by decomposing system tasks. Taking the system task in the above example, the subtasks obtained after decomposing the system task can include optimizing the danger warning task for Park A, material dispatch planning for Park A, and safety generation planning for Park A.

[0114] The capability information required for each subtask refers to the capabilities required to complete each subtask. For example, if the subtask is to optimize the danger warning task for Park A, the corresponding capability information is the danger warning capability; if the subtask is to plan the material dispatch for Park A, the corresponding capability information is the material dispatch capability; if the subtask is to plan the safety generation for Park A, the corresponding capability information is the safety generation capability.

[0115] System support resources refer to the resources that need to be configured to complete each subtask, including but not limited to technical, human and material resources. For example, logical reasoning technology, natural resource understanding technology, knowledge expression technology, intelligent robot technology, machine learning technology, etc.

[0116] Exemplarily, according to the system requirement document, the method of determining multiple modeling attributes of the target intelligent complex system and the attribute description information of each modeling attribute can be to select a modeling attribute from a plurality of preset attributes according to the system requirement document, and then describe the selected modeling attribute according to the attribute description standard of each attribute to obtain the attribute description information of the modeling attribute. For example, the attribute database stores multiple preset attributes, including system planning attributes, summary information attributes, comprehensive dictionary attributes, capability requirement attributes, capability vision attributes, capability classification attributes, capability baseline attributes, capability dependency attributes, capability and task mapping attributes, business concept map attributes, business requirement decomposition attributes, task and rule association relationship attributes, task and organization mapping relationship attributes, capability and component system mapping relationship attributes, resource and business capability attributes, necessary resource attributes, technology classification attributes, etc. Several attributes can be selected from the multiple attributes as modeling attributes, and then the attribute description standard corresponding to each modeling attribute is obtained from the attribute database, and then each modeling attribute is described according to each attribute description standard and the system requirement document to obtain the attribute description information of each modeling attribute.

[0117] S202: Determine the intelligent system architecture of the target intelligent complex system according to each modeling attribute and each attribute description information.

[0118] After obtaining each modeling attribute and the attribute description information corresponding to each modeling attribute, each modeling attribute and the attribute description information corresponding to each modeling attribute can be determined as the intelligent system architecture of the target intelligent complex system.

[0119] In order to ensure that the attribute description information of each modeling attribute is accurate, after obtaining each modeling attribute and the attribute description information corresponding to each modeling attribute, the attribute description information of each modeling attribute can be verified. After the verification is successful, each modeling attribute and the attribute description information corresponding to each modeling attribute are determined as the intelligent system architecture of the target intelligent complex system. Among them, the verification method can be to verify whether each attribute description information is consistent with the keywords in the system requirement document according to the system requirement document. For example, in the system requirement document, in order to build an intelligent complex system for Park A, it is determined whether the word "park" is mentioned in each attribute description information, and whether it is described as Park A.

[0120] S203, constructing a target intelligent complex system based on the intelligent system architecture.

[0121] Exemplarily, a method for constructing a target intelligent complex system based on an intelligent system architecture may be to obtain system construction data corresponding to each attribute description information; fill the system construction data in a corresponding position of the intelligent system architecture to obtain the target intelligent complex system.

[0122] In the embodiment of the present application, the system construction data refers to the task data of multiple subtasks in each attribute description information, the capability data of the capability information required for each subtask, and the resource data of the system support resources. Taking the system support resources as an example, if the system support resources include machine learning technology, it is necessary to obtain the data of the machine learning technology, such as the data related to the machine learning model.

[0123] After obtaining the system construction data corresponding to each attribute description information, the system construction data is filled in the corresponding position of the intelligent system architecture to construct the target intelligent complex system.

[0124] In the intelligent complex system construction method provided in the embodiment of the present application, by responding to the construction request of the target intelligent complex system, according to the system requirements document, multiple modeling attributes of the target intelligent complex system and the attribute description information of each modeling attribute are determined, and then the intelligent system architecture of the target intelligent complex system is determined according to each modeling attribute and each attribute description information, and then the target intelligent complex system is constructed based on the intelligent system architecture, wherein the attribute description information includes multiple subtasks of at least one system task, the capability information required for each subtask and the system support resources. In this method, when it is necessary to construct the target intelligent complex system, starting from the user's needs, according to the system requirements document, the modeling attributes for constructing the target intelligent complex system and the attribute description information of each modeling attribute are determined, so that the tasks to be completed, the capabilities to be possessed and the supporting resources to be supported when constructing the target intelligent complex system are clarified, and then a basic structural framework, i.e., the intelligent system architecture, is preliminarily obtained according to each modeling attribute and each attribute description information. Based on the intelligent system architecture, the target intelligent complex system can be quickly constructed, which provides a unified standard specification for constructing the intelligent complex system and improves the level of flexible adaptation of the intelligent complex system to the needs of intelligent business.

[0125] Based on the above embodiment, an embodiment is provided to illustrate the process of determining multiple modeling attributes of the target intelligent complex system and attribute description information of each modeling attribute according to the system requirement document.

[0126] In an exemplary embodiment, Figure 3 As shown, according to the system requirement document, multiple modeling attributes of the target intelligent complex system and attribute description information of each modeling attribute are determined, including:

[0127] S301, according to multiple layers in the preset intelligent system architecture framework information, obtain multiple layer attributes in each layer and attribute description rules of each layer attribute.

[0128] In the embodiment of the present application, the intelligent system architecture framework information refers to the information within the intelligent system architecture framework. Among them, the intelligent system architecture framework is divided into eight layers, namely: Top-Down Design Layer (TdDL), Business Capability Layer (BCL), Business Logic Layer (BLL), Resource of SoS Layer (RSSL), Intelligent Technology Layer (ITL), Human Factors Layer (HFL), Business Rules Layer (BRL) and Standard Specification and Estimate Layer (SSEL).

[0129] like Figure 4 The figure shows the relationship diagram of all layers of the intelligent system architecture framework. The intelligent system architecture framework (ISSAF) is divided into eight layers: the top-level design layer is used as a comprehensive planning layer to describe the top-level information of the intelligent system related to all levels; the business capability layer is used to describe the capabilities that the intelligent system should have to complete the top-level tasks; the business logic layer is used to describe the business activities and resource information flow during the execution of the intelligent system tasks; the system resource layer is used to describe the key information such as the component systems of the intelligent system; the business rule layer is used to describe the rules that should be followed in the construction and operation of the intelligent system to constrain the expression of each level; the system human factor layer is used to describe the impact of human factors on the system; the standard specification and evaluation layer is used to describe the standards, specifications and evaluation methods of the intelligent system architecture; the intelligent technology layer acts on all layers and is used to describe the role of intelligent technology in the construction of the intelligent system.

[0130] The following is an introduction to the attributes in each layer and the relationship between the attributes in the layer. The following description of the attributes in each layer refers to the attribute description rules of each attribute.

[0131] ① Top-level design layer: The top-level design layer describes the top-level overview of the system architecture related to all levels, provides general information about the intelligent system architecture framework, and generally describes the purpose (such as corporate strategy, mission, corporate layout, etc.), scope, background and related vocabulary of the entire system construction, providing necessary global information for the description of other levels. The top-level design layer consists of three attributes, namely, summary information attribute (TdDL-1), comprehensive dictionary attribute (TdDL-2) and system planning attribute (TdDL-3).

[0132] like Figure 5The figure shows the relationship between the top-level design layer attributes. The top-level design layer starts from the top-level tasks of the intelligent complex system, and briefly describes the overview and summary information of the design, construction, application and management of the intelligent complex system based on the summary information attribute (including the purpose and significance of the development system architecture, project background and other basic information). The comprehensive dictionary attribute collects and defines all the terms used in the design, construction, application and management of the intelligent complex system, and the system planning attribute plans the evolution route of the intelligent complex system and the direction and progress of capability development.

[0133] ② Business capability layer: The business capability layer describes the requirements, conception, structure and other relationships of the intelligent system capabilities from the perspective of the main business capability requirements of the intelligent system to perform the target tasks. The business capability layer consists of six attributes, namely capability requirement attribute (BCL-1), capability vision attribute (BCL-2), capability classification attribute (BCL-3), capability dependency attribute (BCL-4), capability and task mapping attribute (BCL-5) and capability baseline attribute (BCL-6).

[0134] like Figure 6 The figure shows the relationship between attributes in the business capability layer. The business capability layer starts from the perspective of the main business capability requirements for the intelligent complex system to perform its mission tasks, clarifies the top-level capability requirement concept based on the capability requirement attribute, and uses the capability vision attribute to visualize the system's initial capability concept and the final system capability concept achieved through integration or upgrading. The capability classification attribute breaks down the system capability visualized by the capability vision attribute into various sub-capabilities, and uses the capability dependency attribute to explain in detail the relationship between various capabilities defined in the capability classification attribute. The capability and task mapping attribute is used to analyze the relationship between the various capabilities defined in the capability classification attribute and business activities, system resources, and intelligent technologies, and to describe the supporting role for business activities, as well as the supporting role of system resources and intelligent technologies for system capabilities. The capability baseline attribute is used to analyze the initial capability baseline level of each sub-capability defined in the capability classification attribute.

[0135] ③ Business logic layer: The business logic layer describes the enterprise strategy, business rules, business nodes, organizational relationships, association relationships, and information exchange required to support the business process from the perspective of various attribute configurations and information relationships of the intelligent system in the business application process. The business logic layer consists of seven attributes, namely business concept map attribute (BLL-1), organizational relationship attribute (BLL-2), business requirement decomposition attribute (BLL-3), business thread attribute (BLL-4), task and rule association relationship attribute (BLL-5), task and organization mapping relationship (BLL-6) and task and system resource mapping relationship attribute (BLL-7).

[0136] like Figure 7The figure shows the relationship between attributes of the business logic layer. The business logic layer is used to describe the enterprise strategy, business rules, business nodes, organizational relationships, and the information exchange and association relationships required in the process. Based on the business concept map attributes, it quickly and at a high level describes what the intelligent system should do and how to do it. With the help of the business requirement decomposition attributes, the top-level tasks involved in the business concept map attributes are broken down into subtasks, and the hierarchical relationship between subtasks is described. The business thread attributes describe the input and output relationships of different subtasks decomposed by the business requirement decomposition attributes one by one, and assign them to specific business activities. The task and rule association relationship attributes, the item and organization mapping relationship attributes, and the task and system resource mapping relationship attributes are used to analyze the mapping relationship between different subtasks decomposed by the business requirement decomposition attributes and system rules, organizations, and system resources.

[0137] ④ System resource layer: The system resource layer describes the system's component system composition, connection relationship, communication relationship, interface characteristics, correspondence with business activities, correspondence with capabilities, performance parameters, key technology development ideas, etc. from the perspective of the system's components and their relationships. Combined with the business capability layer, it can explain the component system implementation and deployment issues that support business needs. The system resource layer consists of nine attributes, namely component system classification attributes (RSSL-1), component system capability attributes (RSSL-2), component system interface attributes (RSSL-3), component system performance parameter attributes (RSSL-4), component system interaction relationship attributes (RSSL-5), capability and component system mapping relationship attributes (RSSL-6), component system state transition attributes (RSSL-7), required resource attributes (RSSL-8) and resource and business capability relationship attributes (RSSL-9).

[0138] like Figure 8As shown in the figure, it is the relationship between the attributes of the system resource layer. The system resource layer determines the category and specific composition of the intelligent system component system that meets the requirements based on the classification attributes of the component system from the perspective of the components of the system and their relationships, and describes the specific capability composition and capability requirements of the component system by the capability attributes of the component system. The interface attributes of the component system describe the interface relationship between the component systems based on the classification attributes of the component system. The performance parameter attributes of the component system quantitatively describe the key performance of the component system based on the classification attributes of the component system. The interactive relationship attributes of the component system describe the exchanged resources, the standards and specifications followed, the rules and mechanisms of interaction, etc. based on the classification attributes of the component system, but do not describe the specific physical implementation of the interactive relationship. This layer describes the supporting relationship between the component system and the capability classification attributes described in the component system classification attributes based on the mapping relationship attributes between the capability and the component system. The state transition attributes of the component system are used to illustrate the orderly action of the component system function transfer described by the component system capability attributes, and can also reflect the response order of a certain function to a specific component system. The necessary resource attributes are used to describe the resource elements such as human resources, rule lists, standard specifications, information resources, system resources and environmental resources required by the intelligent complex system. The resource-business capability relationship attribute is used to illustrate the correspondence between required resources and system capabilities.

[0139] ⑤ Intelligent technology layer: The intelligent technology layer describes the impact of intelligent technology on the construction of intelligent systems and future system management from the aspects of technology system composition, technology development forecast and technology impact. The intelligent technology layer consists of three attributes, namely technology classification attribute (ITL-1), component system to technology mapping matrix attribute (ITL-2) and technology dependency relationship attribute (ITL-3).

[0140] like Fig. 9 The figure shows the relationship between the attributes of the intelligent technology layer. The intelligent technology layer describes the relevant technologies involved in the design, construction, application, and management of intelligent complex systems from the perspectives of technology system composition, technology development forecast, and technology impact, based on technology classification attributes, and describes the supporting relationship between intelligent technologies and component systems in the component system classification attributes from the component system to technology mapping matrix attributes. The technology association relationship attributes describe in detail the supporting relationship between technologies defined in the technology classification attributes.

[0141] ⑥ System human factors layer: The system human factors layer describes the role of people in the system, and is used to capture the demand for personnel in the construction and operation of the intelligent system, and to clarify the interaction between people and between people and the component systems that make up the intelligent system. The system human factors layer consists of five attributes, namely, the organization classification attribute (HFL-1), the organization command relationship attribute (HFL-2), the organization collaboration relationship attribute (HFL-3), the organization and activity association attribute (HFL-4), and the human-computer interaction association attribute (HFL-5).

[0142] like Fig.10 As shown in the figure, it is the relationship between the attributes of the human factor layer of the system. The human factor layer of the system starts from the perspective of describing the role of people in the intelligent complex system. Based on the organizational classification attributes, it describes the authority and responsibilities of organizations at all levels, command levels, departments, positions, etc., and the command relationship between organizations is described by the organizational command relationship attribute, and the collaborative relationship between organizations is described by the organizational collaboration relationship attribute. The organization and activity association attributes describe the business activities related to the organization throughout the life cycle of the intelligent complex system, and clearly define the personnel roles in the organization classification attributes as the executors of the activities. The human-computer interaction association attributes mainly analyze the interaction between the personnel roles in the organization classification attributes and the relevant component systems when completing relevant activities.

[0143] ⑦ Business rule layer: The business rule layer describes various task execution rules and component system application rules in the business process based on the business needs of the intelligent system. The business rule layer consists of three attributes, namely, the system rule classification attribute (BRL-1), the rule description attribute (BRL-2), and the rule combination description attribute (BRL-3).

[0144] like Fig.11 The figure shows the relationship between attributes in the business rule layer. The business rule layer starts from the business needs of the intelligent complex system and describes the rules that should be followed in the design, construction, application, and management of the intelligent complex system based on the system rule classification attributes. The rule description model describes the detailed execution process of each type of rule in detail. The rule combination description attribute describes a more complex system rule that is composed of various basic rules in the system rule classification attributes.

[0145] ⑧ Standard Specification and Evaluation Layer: The Standard Specification and Evaluation Layer describes the standards, specifications, and prediction and evaluation methods that can be applied to the intelligent system. The Standard Specification and Evaluation Layer consists of four attributes, namely, the Standard Overview Attribute (SSEL-1), the Standard System Attribute (SSEL-2), the Standard Prediction Attribute (SSEL-3), and the System Evaluation Attribute (SSEL-4).

[0146] like Fig.12 As shown in the figure, it is the relationship between the attributes of the standard specification and the evaluation layer. Based on the standard overview attribute, the standard specification and evaluation layer provides an overview of all relevant technical standards, specifications and protocols in the process of designing, building, using and managing intelligent complex systems, and is described in detail by the standard system attribute. The standard prediction attribute is a supplement to the standard system attribute. The regular prediction of the standard helps relevant personnel to predict the impact of various technical implementation progress in the process of designing, building, using and managing intelligent complex systems. The system evaluation attribute is an evaluation of whether the various indicators in the process of designing, building, using and managing intelligent complex systems meet the top-level task requirements.

[0147] In addition to the above, the intelligent complex system architecture framework includes Figure 5-Figure 12 The following is an introduction to the inter-layer attribute association relationship in the intelligent complex system architecture framework.

[0148] ① The relationship between the top-level design layer and other layer attributes.

[0149] like Fig.13 As shown in the figure, it is a relationship diagram of the top-level design layer's effect on the attributes of other layers. There is a correlation between the top-level design layer and the attributes of the business capability layer, business logic layer, intelligent technology layer, and standards and specifications and evaluation layer. Among them, the top-level design layer drives the capability requirement attributes of the business capability layer to analyze the mission tasks, and at the same time drives the business concept map attributes of the business logic layer to describe the grand blueprint of the intelligent complex system at the macro level; the top-level design layer drives the technical optimization and development of the intelligent technology layer, and also drives the system evaluation attributes of the standards and specifications and evaluation layer to update and iterate according to the mission tasks.

[0150] Fig.14 As shown in the figure, it is a relationship diagram of the effect of other layer attributes on the top-level design layer. The attributes of the intelligent technology layer and the standard specification and evaluation layer act on the top-level design layer. Among them, the intelligent technology layer promotes the optimization and development of the top-level design layer attributes based on its cutting-edge and advanced technology; the system evaluation attributes of the standard specification and evaluation layer are used to evaluate whether the intelligent complex system meets the top-level tasks.

[0151] ② The relationship between the business capability layer and other layer attributes.

[0152] like Fig.15 The figure shows the relationship between the business capability layer and the attributes of other layers. There is a correlation between the business capability layer and the attributes of the system human factor layer, intelligent technology layer, business logic layer and system resource layer. Among them, the capability requirement attribute of the business capability layer puts forward personnel requirements for the organizational classification attribute of the system human factor layer, puts forward technical requirements for the technical classification attribute of the intelligent technology layer, and puts forward task requirements for the business requirement decomposition attribute of the business logic layer; the capability and task mapping attribute of the business capability layer also puts forward task requirements for the business requirement decomposition attribute of the business logic layer, and puts forward technical requirements for the technical classification attribute of the intelligent technology layer; in addition, the capability baseline attribute of the business capability layer puts forward resource requirements for the component system classification attribute of the system resource layer, and the capability and task mapping attribute of the business capability layer puts forward resource requirements for the component system classification attribute, component system capability attribute, capability and component system mapping relationship attribute and resource and business capability relationship attribute of the system resource layer.

[0153] like Fig.16As shown in the figure, it is a relationship diagram of the effects of other layer attributes on the business capability layer. The attributes of the top-level design layer, system human factors layer, intelligent technology layer, business logic layer and system resource layer act on the business capability layer. Among them, the top-level design layer guides the capability demand analysis of the business capability layer; the organizational classification attributes of the system human factors layer provide personnel guarantee for the capability demand attributes of the business capability layer; the technical classification attributes of the intelligent technology layer provide technical support for the capability classification attributes and capability and task mapping attributes of the business capability layer; the business requirement decomposition attributes of the business logic layer refine the requirements for the capability and task mapping attributes of the business capability layer. In addition, the component system classification attributes of the system resource layer are the capability baseline attributes of the business capability layer, and the capability and component system mapping relationship attributes, resource and component system mapping relationship attributes and component system capability attributes of the system resource layer provide resource guarantee for the capability classification attributes and capability and task mapping attributes of the business capability layer.

[0154] ③ The relationship between the business logic layer and other layer attributes.

[0155] like Fig.17 The figure shows the relationship between the business logic layer and the attributes of other layers. There is a correlation between the attributes of the business logic layer and the intelligent technology layer, business capability layer, system human factors layer, system resource layer and business rule layer. The business requirement decomposition attribute of the business logic layer puts forward technical requirements for the intelligent technology layer, and puts forward task refinement requirements for the capability and task mapping attributes of the business capability layer, and puts forward personnel requirements for the organization and activity association attributes of the system human factors layer; the task and rule association relationship attributes of the business logic layer promote the rule update of the business rule layer; the task and system resource mapping relationship attributes of the business logic layer put forward resource requirements for the component system classification attributes of the system resource layer, and puts forward interaction requirements for the component system interface attributes.

[0156] like Fig.18 As shown in the figure, it is a relationship diagram of the effects of other layer attributes on the business logic layer. The attributes of the top-level design layer, intelligent technology layer, business capability layer, system human factors layer, system resource layer and business rule layer act on the business logic layer. Among them, the top-level design layer guides the business concept diagram attribute design of the business logic layer; the technical classification attributes of the intelligent technology layer provide technical support for the business demand decomposition attributes of the business logic layer; the capability and task mapping attributes of the business capability layer provide capability traction for the business demand decomposition attributes of the business logic layer; the organization and activity association attributes of the system human factors layer provide personnel role analysis for the business demand decomposition attributes of the business logic layer; in addition, the business rule layer constrains the relevant behaviors of the business logic layer; the component system classification attributes and component system interface attributes of the system resource layer provide resource guarantee and interaction relationship representation for the task and system resource mapping relationship attributes of the business logic layer.

[0157] ④ The relationship between the system resource layer and other layer attributes.

[0158] like Fig.19 As shown in the figure, it is a relationship diagram of the system resource layer's effect on the attributes of other layers. There is a correlation between the system resource layer and the attributes of the intelligent technology layer, business capability layer, system human factors layer, and business logic layer. The component system classification attribute of the system resource layer puts forward technical requirements for the component system to technology mapping matrix attribute of the intelligent technology layer, and guarantees the command elements of the organization command relationship attribute of the system human factors layer and the collaboration elements of the organization collaboration relationship attribute. The component system interface attribute of the system resource layer identifies the interactive relationship for the task and system resource mapping relationship attribute of the business logic layer, and the component system classification attribute of the system resource layer provides resource guarantee for the task and system resource mapping relationship attribute of the business logic layer. In addition, the component system classification attribute of the system resource layer provides capability analysis for the capability baseline attribute of the business capability layer. The capability and component system mapping relationship attribute of the system resource layer provides resource support for the capability classification attribute of the business capability layer, the component system capability attribute of the system resource layer provides resource support for the capability and task mapping attribute of the business capability layer, and the resource and business capability relationship attribute of the system resource layer provides resource support for the capability classification attribute of the business capability layer.

[0159] like Fig. 20 As shown in the figure, it is a relationship diagram of the effects of other layer attributes on the system resource layer. The attributes of the intelligent technology layer, the system human factor layer, the business logic layer, and the business capability layer act on the system resource layer. Among them, the component system to technology mapping matrix attribute of the intelligent technology layer provides technical support for the component system classification attribute of the system resource layer; the organizational command relationship attribute and the organizational collaboration relationship attribute of the system human factor layer provide command relationship analysis and collaboration relationship analysis for the component system classification attribute of the system resource layer respectively. The task and system resource mapping relationship attribute of the business logic layer provides interaction requirements for the component system interface attribute of the system resource layer and resource requirements for the component system classification attribute. The capability classification attribute of the business capability layer provides resource requirements for the capability and component system mapping relationship attribute and the resource and business capability relationship attribute of the system resource layer. In addition, the capability and task mapping attribute of the business capability layer provides resource capability requirements for the component system capability attribute of the system resource layer, and the capability baseline attribute provides capability baseline assessment for the component system classification attribute.

[0160] ⑤ The relationship between the intelligent technology layer and other layer attributes.

[0161] As shown in Figure 21, it is a relationship diagram of the intelligent technology layer's effect on other layer attributes. There is a correlation between the intelligent technology layer and the attributes of the top-level design layer, business logic layer, business rule layer, system resource layer, business capability layer, and standard specification and evaluation layer. Among them, the intelligent technology layer drives the optimization and development of the top-level design layer attributes; the technical classification attributes of the intelligent technology layer provide technical support for the business demand decomposition attributes of the business logic layer; the technical dependency attributes of the intelligent technology layer promote the rule update of the business rule layer; the component system to technology mapping matrix attributes of the intelligent technology layer provide technical support analysis for the component system classification attributes of the system resource layer; the technical classification attributes of the intelligent technology layer provide technical support for the capability classification attributes of the business capability layer, and provide technical capability analysis for the capability and task mapping attributes of the business capability layer, and also provide evaluation technical support for the system evaluation attributes of the standard specification and evaluation layer.

[0162] As shown in Figure 22, it is a relationship diagram of the effects of other layer attributes on the intelligent technology layer. The attributes of the top-level design layer, business logic layer, business rule layer, system resource layer, business capability layer, and standard specification and evaluation layer act on the intelligent technology layer. Among them, the top-level design layer drives the optimization and development of the intelligent technology layer; the business demand decomposition attributes of the business logic layer put forward technical requirements for the technical classification attributes of the intelligent technology layer; the business rule layer provides standard guidance and rule constraints for the technical dependency attributes of the intelligent technology layer. In addition, the component system classification attributes of the system resource layer put forward technical requirements for the component system to technology mapping matrix attributes of the intelligent technology layer, and the capability classification attributes and capability and task mapping attributes of the business capability layer put forward technical requirements for the technology classification attributes. The system evaluation attributes of the standard specification and evaluation layer provide evaluation support for the technical level of the technical classification attributes of the intelligent technology layer.

[0163] ⑥ The relationship between the system’s human factors layer and the attributes of other layers.

[0164] As shown in Figure 23, it is a relationship diagram of the system human factors layer's effect on the attributes of other layers. There is a correlation between the system human factors layer and the attributes of the business logic layer, business capability layer, and system resource layer. Among them, the organizational command relationship attribute of the system human factors layer clarifies the command relationship for the organizational system classification attribute of the system resource layer; the organizational collaboration relationship attribute of the system human factors layer clarifies the collaboration relationship for the organizational system classification attribute of the system resource layer; the organization and activity association attribute of the system human factors layer clarifies the human role for the business requirement decomposition attribute of the business logic layer, and at the same time, the organizational classification attribute of the system human factors layer provides personnel guarantee for the capability requirement attribute of the business capability layer.

[0165] As shown in Figure 24, it is a relationship diagram of the effects of other layer attributes on the system human factors layer. The attributes of the business logic layer, business capability layer, and system resource layer act on the system human factors layer. Among them, the business demand decomposition attribute of the business logic layer provides personnel demand analysis for the organization and activity association attribute of the system human factors layer; the capability demand attribute of the business capability layer proposes personnel demand for the organization classification attribute of the system human factors layer; the component system classification attribute of the system resource layer provides resource element support for the organization command relationship attribute and organization collaboration relationship attribute of the system human factors layer.

[0166] ⑦ The relationship between the business rule layer and other layer attributes.

[0167] As shown in Figure 25, it is a relationship diagram of the business rule layer's effect on other layer attributes. There is an association between the business rule layer and the attributes of the intelligent technology layer and the business logic layer. Among them, the business rule layer constrains the relevant rules for the task and rule association attributes of the business logic layer; the business rule layer provides standard guidance and rule constraints for the technical dependency attributes of the intelligent technology layer.

[0168] As shown in Figure 26, it is a relationship diagram of the effects of other layer attributes on the business rule layer. The attributes of the business logic layer and the intelligent technology layer act on the business rule layer. Among them, the task and rule association attributes of the business logic layer and the technical dependency relationship of the intelligent technology layer provide timely rule updates for the business rule layer.

[0169] ⑧ The relationship between the standards, specifications and assessment layers and other layer attributes.

[0170] As shown in Figure 27, it is a relationship diagram of the standard specification and evaluation layer's effect on other layer attributes. There is a correlation between the standard specification and evaluation layer and the attributes of the intelligent technology layer and the top-level design layer. Among them, the standard system attributes of the standard specification and evaluation layer provide standard guidance for the technical dependency attributes of the intelligent technology layer; the system evaluation attributes of the standard specification and evaluation layer provide technical level evaluation capabilities for the technical classification attributes of the intelligent technology layer; in addition, the system evaluation attributes of the standard specification and evaluation layer evaluate whether the designed intelligent complex system meets the top-level task requirements for the top-level design layer.

[0171] As shown in Figure 28, it is a relationship diagram of the effects of other layer attributes on the standard specification and evaluation layer. The attributes of the intelligent technology layer and the top-level design layer act on the standard specification and evaluation layer. Among them, the technical dependency attribute of the intelligent technology layer timely updates the technical standards for the standard system attribute of the standard specification and evaluation layer; the technical classification attribute of the intelligent technology layer provides technical support for the system evaluation attribute of the standard specification and evaluation layer; in addition, the top-level design layer provides support for the update of evaluation elements for the system evaluation attribute of the standard specification and evaluation layer.

[0172] Exemplarily, each layer in the intelligent system architecture framework information can be obtained, and then based on each layer, multiple attributes in the layer and attribute description rules of each attribute can be obtained as multiple layer attributes and attribute description rules of each layer attribute.

[0173] S302, determining each modeling attribute according to the system requirement document and each layer attribute.

[0174] When obtaining each modeling attribute, several layer attributes may be selected from a plurality of layer attributes according to information in the system requirement document and determined as each modeling attribute.

[0175] Based on this, according to the system requirement document and the attributes of each layer, the way to determine each modeling attribute can be to obtain the implementation functions, application fields and application modes of the target intelligent complex system according to the system requirement document; according to the implementation functions, application fields and application modes, the business requirement decomposition attributes, capability classification attributes and required resource attributes in each layer attribute are determined as each modeling attribute.

[0176] The system requirements document records the functions, application fields, and application modes that the target intelligent complex system needs to achieve. Based on this information, the modeling attributes can be determined from the above-mentioned multiple layer attributes. In the embodiment of the present application, the business demand decomposition attributes, capability classification attributes, and required resource attributes in each layer attribute are determined as each modeling attribute. These three attributes are usually indispensable when building an intelligent complex system. For the remaining attributes in the layer attributes, the required attributes can be selected according to actual needs to build the target intelligent complex system.

[0177] It should be noted that when determining each modeling attribute, in addition to considering the system requirement document, more comprehensive and accurate modeling attributes can be determined by fully considering historical experience, rules, expert knowledge and other factors to improve the reliability and robustness of the system architecture in practical applications.

[0178] S303: Determine attribute description information of each modeling attribute based on the attribute description rules of each modeling attribute and each layer attribute.

[0179] After each modeling attribute is determined, the attribute description rule corresponding to each modeling attribute can be obtained from the attribute description rule of each layer attribute, and each modeling attribute can be specifically described according to the attribute description rule corresponding to each modeling attribute and the information in the system requirement document to obtain the attribute description information of each modeling attribute.

[0180] In the intelligent complex system construction method provided by the embodiment of the present application, multiple layer attributes in each layer and the attribute description rules of each layer attribute are obtained according to multiple layers in the preset intelligent system architecture framework information, and then each modeling attribute is determined according to the system requirement document and each layer attribute, and then the attribute description information of each modeling attribute is determined based on the attribute description rules of each modeling attribute and each layer attribute. In this method, by introducing the intelligent system architecture framework, data support is provided for determining the modeling attributes and attribute description information, so that the computer device can determine the modeling attributes from the multiple layer attributes in the intelligent system architecture framework, and determine the attribute description information of the modeling attributes according to the attribute description rules of each layer attribute; and when determining the modeling attributes, the system requirement documents, historical experience, rules and expert knowledge are fully considered, so that the modeling attributes are more comprehensive and accurate.

[0181] Based on the above embodiment, an embodiment is provided to illustrate the process of determining the attribute description information of each modeling attribute based on the attribute description rules of each modeling attribute and each layer attribute.

[0182] In an exemplary embodiment, as shown in FIG. 29 , each modeling attribute includes a business requirement decomposition attribute, a capability classification attribute, and a required resource attribute; based on the attribute description rules of each modeling attribute and each layer attribute, the attribute description information of each modeling attribute is determined, including:

[0183] S401, according to the attribute description rules of each layer attribute, obtain the attribute description rules of the business requirement decomposition attribute, the attribute description rules of the capability classification attribute and the attribute description rules of the required resource attribute.

[0184] The intelligent system architecture framework includes attribute description rules for different layer attributes, directly obtains attribute description rules for business requirement decomposition attributes in layer attributes, attribute description rules for capability classification attributes, and attribute description rules for required resource attributes.

[0185] S402, determining attribute description information of the business requirement decomposition attribute according to the system requirement document and the attribute description rule of the business requirement decomposition attribute.

[0186] The attribute description rule of the business requirement decomposition attribute is to break down the top-level task into subtasks and describe the hierarchical relationship between the subtasks. Therefore, when determining the attribute description information of the business requirement decomposition attribute, it is necessary to decompose the system tasks of the target intelligent complex system.

[0187] Based on this, in one of the embodiments, the system tasks of the target intelligent complex system in the system requirement document are decomposed to obtain multiple subtasks of the target intelligent complex system; each subtask is described according to the attribute description rules of the business requirement decomposition attributes to obtain subtask description information; and the subtask description information is used as the attribute description information of the business requirement decomposition attributes.

[0188] Exemplarily, the system task of the target intelligent complex system in the system requirement document is decomposed to obtain multiple subtasks of the target intelligent complex system by displaying a task decomposition interface, wherein the task decomposition interface includes multiple candidate subtasks, and the multiple candidate subtasks include historical subtasks and preset subtasks. The user can select the target subtask from the multiple candidate subtasks and click to confirm. The computer device can obtain the target subtask selected by the user in the task decomposition interface, and determine the target subtask as the subtask after the system task is decomposed, that is, multiple subtasks of the target intelligent complex system are obtained. Among them, a subtask filling area can also be provided in the task decomposition interface. If there is no subtask required by the user among the multiple candidate subtasks, the user can decompose the system task according to actual needs, and fill in the decomposed subtasks in the subtask filling area, and the subtask filled in by the user is determined as the subtask of the target intelligent complex system.

[0189] After decomposing to obtain multiple subtasks, the decomposed subtasks can be described according to the attribute description rules of the business demand decomposition attributes to obtain subtask description information, and the subtask description information can be determined as the attribute description information of the business demand decomposition attributes. Taking the tasks of the aforementioned A park as an example, the attribute description information of the business demand decomposition attributes can be shown in Figure 30, where the system task-smart park system is first decomposed into first-level subtasks-hazard warning, material scheduling, safe production and energy transportation, and then decomposed into second-level subtasks-park real-time monitoring, dangerous goods management, dangerous goods transportation planning, material management, material scheduling planning, energy management, production monitoring, intelligent auxiliary decision-making, energy management and energy transportation planning. It should be noted that when decomposing system tasks, the system tasks can be stopped by continuously decomposing them into meta-tasks. Among them, meta-tasks refer to sub-tasks that can no longer be decomposed. Alternatively, the subtasks can also be described in the following Table 1 (Table 1 only takes the first-level subtasks as an example).

[0190] Table 1

[0191]

[0192] In this embodiment, the system tasks are decomposed into smaller, manageable task units (subtasks) to facilitate the realization of various capabilities of the support system. At the same time, the association and interaction between the task units are determined to ensure that they can work together. The key to this process is to ensure that each task unit can operate independently and effectively interact with other task units when necessary to provide support for the efficient operation of the entire system.

[0193] S403: Determine attribute description information of the capability classification attribute according to the attribute description rule of the capability classification attribute.

[0194] The attribute description rule of capability classification attributes is to decompose the system capability into various sub-capabilities. Therefore, when determining the attribute description information of capability classification attributes, it is necessary to decompose the system capability of the target intelligent complex system.

[0195] Based on this, in one of the embodiments, the system capability of the target intelligent complex system is decomposed according to the task capability knowledge base and multiple sub-tasks of the target intelligent complex system to obtain multiple sub-capabilities of the target intelligent complex system; each sub-capability is described according to the attribute description rules of the capability classification attributes to obtain sub-capability description information; and the sub-capability description information is used as the attribute description information of the capability classification attributes.

[0196] In the embodiment of the present application, meta-capabilities are defined in the task capability knowledge base, and a relationship model between meta-tasks and meta-capabilities is constructed, wherein meta-capabilities refer to sub-capabilities that cannot be further decomposed.

[0197] Exemplarily, according to the multiple subtasks of the target intelligent complex system, the meta-capabilities corresponding to each subtask can be matched from the relational model in the task capability knowledge base, and the matched multiple meta-capabilities can be determined as the multiple sub-capabilities of the target intelligent complex system. It should be noted that if there is no sub-capability corresponding to a certain subtask in the task capability knowledge base, a sub-capability filling interface can be displayed to the user, and the user can enter the sub-capability corresponding to the subtask in the sub-capability filling interface according to actual business needs.

[0198] After obtaining multiple sub-capabilities of the target intelligent complex system, each sub-capability is described according to the attribute description rules of the capability classification attribute to obtain sub-capability description information, and the sub-capability description information is determined as the attribute description information of the capability classification attribute.

[0199] In this example, the system capability requirements are decomposed in an orderly manner into smaller, implementable capability units (sub-capabilities). Through this process, the team decomposes the overall capabilities of the system into manageable parts, ensuring that each capability unit can be effectively designed, implemented, and tested, which helps improve the modularity and maintainability of the system and makes the development process more flexible and controllable. Through clear and systematic decomposition, the team can better understand and manage various aspects of the system, providing a clear roadmap for the subsequent construction phase.

[0200] S404: Determine attribute description information of the essential resource attributes according to the attribute description rule of the essential resource attributes.

[0201] In one embodiment, the system support resources of the target intelligent complex system are determined based on the capability resource knowledge base and multiple sub-capabilities of the target intelligent complex system; the system support resources are described according to the attribute description rules of the essential resource attributes to obtain resource description information; and the resource description information is determined as the attribute description information of the essential resource attributes.

[0202] In the embodiment of the present application, the capability resource knowledge base defines various equipment and element resources, and constructs a relationship model between resources and meta-capabilities.

[0203] For example, according to the multiple sub-capabilities of the target intelligent complex system, resources corresponding to each sub-capability can be matched from the relational model in the capability resource knowledge base, and the matched multiple resources can be determined as the system support resources of the target intelligent complex system. It should be noted that if there is no system support resource corresponding to a certain sub-capability in the capability resource knowledge base, a resource filling interface can be displayed to the user, and the user can enter the resource corresponding to the sub-capability in the resource filling interface according to actual business needs.

[0204] After obtaining the system support resources of the target intelligent complex system, the system support resources are described according to the attribute description rules of the essential resource attributes to obtain resource description information, and the resource description information is determined as the attribute description information of the essential resource attributes.

[0205] In addition, if the modeling attributes include capability and intelligent technology mapping matrix elements, the corresponding attribute description information can be shown in Table 2 below.

[0206] Table 2

[0207]

[0208] If the modeling attributes include capability baseline attributes, the corresponding attribute description information may be as shown in Table 3 below.

[0209] Table 3

[0210]

[0211] If the modeling attribute includes the component system classification attribute, the corresponding attribute description information can be shown in Figure 31 below. Among them, the component system categories of the target intelligent complex system include energy component system, logistics component system, security component system, environmental protection component system and geographic information component system. If the modeling attribute includes the component system to technology mapping matrix attribute, the corresponding attribute description information can be shown in Table 4 below.

[0212] Table 4

[0213]

[0214] In this embodiment, the various supporting resources required by the system are clearly defined, including but not limited to technical, human and material resources. Users need to carefully organize and configure these resources to ensure that they can effectively support the design and development of the system. At the same time, ensure the adequacy and effective use of resources, organize and configure these supporting resources, effectively support the development and implementation of the system, and improve the execution efficiency and success possibility of the project.

[0215] In the intelligent complex system construction method provided by the embodiment of the present application, the attribute description rules of the business requirement decomposition attributes, the attribute description rules of the capability classification attributes, and the attribute description rules of the required resource attributes are obtained according to the attribute description rules of each layer attribute, and then the attribute description information of the business requirement decomposition attributes is determined according to the system requirement document and the attribute description rules of the business requirement decomposition attributes, the attribute description information of the capability classification attributes is determined according to the attribute description rules of the capability classification attributes, and the attribute description information of the required resource attributes is determined according to the attribute description rules of the required resource attributes. In this method, by obtaining the attribute description rules of the business requirement decomposition attributes, the attribute description rules of the capability classification attributes, and the attribute description rules of the required resource attributes, a basis is provided for determining the attribute description information, so that the computer device can describe each modeling attribute based on these attribute description rules, obtain the attribute description information of each modeling attribute, and provide data support for generating the intelligent system architecture of the target intelligent complex system.

[0216] Based on any of the above embodiments, an embodiment is provided to illustrate the process of determining the intelligent system architecture of the target intelligent complex system based on each modeling attribute and each attribute description information.

[0217] In an exemplary embodiment, as shown in FIG32 , the intelligent system architecture of the target intelligent complex system is determined according to each modeling attribute and each attribute description information, including:

[0218] S501, determining the initial intelligent system architecture of the target intelligent complex system according to each modeling attribute and each attribute description information.

[0219] The initial intelligent system architecture refers to an initial, unverified system architecture obtained based on each modeling attribute and each attribute description information.

[0220] After obtaining each modeling attribute and the attribute description information of each modeling attribute, each modeling attribute and the attribute description information of each modeling attribute are stored in a document to obtain an initial intelligent system architecture of the target intelligent complex system.

[0221] S502, verifying the initial intelligent system architecture to obtain the intelligent system architecture.

[0222] After obtaining the initial intelligent system architecture, the logic, methods and quality of the system architecture are verified from different angles to ensure that the system meets actual business needs.

[0223] Exemplarily, the initial intelligent system architecture is verified to obtain the intelligent system architecture by performing data completeness verification on the initial intelligent system architecture to obtain a candidate intelligent system architecture; and performing data consistency verification on the candidate intelligent system architecture according to each modeling attribute and each attribute description information to obtain the intelligent system architecture.

[0224] Among them, data integrity verification refers to the verification method to determine whether the data in the intelligent system architecture is complete. Data consistency verification refers to the verification method to determine whether the terminology in the intelligent system architecture is consistent.

[0225] In one of the embodiments, the data completeness of the initial intelligent system architecture is verified, and a method for obtaining a candidate intelligent system architecture can be to model and simulate the initial intelligent system architecture to obtain a virtual intelligent complex system corresponding to the initial intelligent system architecture; run the virtual intelligent complex system; if the virtual intelligent complex system runs normally, the initial intelligent system architecture is determined to be the candidate intelligent system architecture.

[0226] In the embodiments of the present application, simulation software can be used to model and simulate the initial intelligent system architecture to obtain a virtual intelligent complex system of the simulated initial intelligent system architecture, and the virtual intelligent complex system can be run to determine whether the virtual intelligent complex system can operate normally. If the virtual intelligent complex system operates normally, the initial intelligent system architecture is determined to be a candidate intelligent system architecture. Among them, the method of running the virtual intelligent complex system can be to pre-set the operation task, for example, any two different component systems send messages to each other. If the messages sent between the two component systems are accurate, it is determined that the virtual intelligent complex system is operating normally. Otherwise, it is determined that the virtual intelligent complex system is operating abnormally. It should be noted that the method of running the virtual intelligent complex system or the implementation method of the operation task is not limited to the above examples, and the embodiments of the present application do not limit this.

[0227] In the embodiment of the present application, when the virtual intelligent complex system runs abnormally, the intelligent system architecture can also be adjusted and corrected. In one embodiment, if the virtual intelligent complex system runs abnormally, the virtual intelligent complex system is adjusted; the initial intelligent system architecture adjusted synchronously with the virtual intelligent complex system is obtained; and the adjusted initial intelligent system architecture is determined as the candidate intelligent system architecture.

[0228] In this embodiment, the virtual intelligent complex system is associated with the initial intelligent system architecture. When the virtual intelligent complex system is adjusted, the corresponding part of the initial intelligent system architecture will also be adjusted. Therefore, in the embodiment of the present application, if the virtual intelligent complex system runs abnormally, the user can adjust the virtual intelligent complex system, and the information corresponding to the adjusted part in the initial intelligent system architecture will also be automatically adjusted. At this time, the initial intelligent system architecture adjusted synchronously with the virtual intelligent complex system is obtained, and the adjusted initial intelligent system architecture is determined as the candidate intelligent system architecture.

[0229] In one of the embodiments, the method for verifying data consistency of the candidate intelligent system architecture can be to perform data consistency verification on the modeling attributes within the same layer and the modeling attributes associated between different layers based on the description information of each attribute; if the key information in the modeling attributes within the same layer is consistent, and the key information of the modeling attributes associated between different layers is consistent, then the candidate intelligent system architecture is determined to be the intelligent system architecture; if there is inconsistent information in the key information in the modeling attributes within the same layer and the key information of the modeling attributes associated between different layers, then adjust the attribute description information, and determine the intelligent system architecture based on the adjusted attribute description information.

[0230] In the embodiment of the present application, verification is performed based on the aforementioned intra-layer attribute relationship and inter-layer attribute association relationship. For modeling attributes within the same layer, the attribute description information of the modeling attributes within the same layer is verified to determine whether the key information in each attribute description information is consistent, that is, to determine whether the description terms for the same concept in each attribute description information are consistent. For modeling attributes that are associated between different layers, the attribute description information of the two associated modeling attributes is also verified to determine whether the key information in the two attribute description information is consistent, that is, to determine whether the descriptions of the same concept in the two attribute description information are consistent. For example, for the term "danger monitoring", it should be described as danger monitoring. If the words "danger monitoring" and so on appear, it is determined to be inconsistent.

[0231] If the key information in the modeling attributes within the same layer is consistent, and the key information of the modeling attributes associated between different layers is consistent, the current candidate intelligent architecture is determined as the intelligent architecture.

[0232] If there is inconsistency between the key information of the modeling attributes in the same layer and the key information of the modeling attributes associated between different layers, it is necessary to adjust the inconsistent attribute description information and determine the intelligent system architecture based on the adjusted attribute description information.

[0233] In the embodiment of the present application, the candidate intelligent system architecture can also be checked for logical rationality. Among them, the method of logical rationality check can be for the modeling attributes that propose technical requirements, task requirements, personnel requirements and other requirements, whether there are corresponding modeling attributes to support the requirements. Taking the above-mentioned business capability layer on other layer attributes as an example, if the modeling attributes in the embodiment of the present application include capability requirement attributes, and according to the relationship diagram, it can be seen that the capability requirement attributes propose personnel requirements, and the personnel requirements need to be supported by the organizational classification attributes in the human factors layer of the system, then it is determined whether the modeling attributes in the embodiment of the present application include the modeling attribute of the organizational classification attribute. If so, the logic is reasonable, otherwise, the logic is unreasonable. When the logic is unreasonable, it is necessary to determine the layer attributes that should support a certain requirement as modeling attributes, describe them, and add them to the intelligent system architecture to obtain an accurate intelligent system architecture.

[0234] This embodiment provides a clear understanding of the interaction between the attributes of each layer of the architecture through the logic rationality verification of the architecture, so as to more comprehensively understand the input, output, dependency and mutual constraint relationship of each attribute. This process helps to verify the rationality of the business process and system design process, and determine whether the designed system can operate as expected. It also helps to identify potential design conflicts, bottlenecks and loopholes, and provides strong support for the optimization and evolution of intelligent complex systems.

[0235] In the intelligent complex system construction method provided in the embodiment of the present application, the initial intelligent system architecture of the target intelligent complex system is determined according to each modeling attribute and each attribute description information, and then the initial intelligent system architecture is verified to obtain the intelligent system architecture. In this method, after the initial intelligent system architecture is determined according to each modeling attribute and each attribute description information, the logic, method and quality of the system architecture are verified from different angles, so that the intelligent complex system can better meet the actual business needs, effectively improve the information management efficiency and data quality of the entire system, and thus improve the overall performance of the entire intelligent complex system.

[0236] In addition, in an exemplary embodiment, the present application also provides a method for constructing an intelligent complex system, as shown in FIG33 , which may include the following steps:

[0237] S601, in response to a request to build a target intelligent complex system, obtain multiple layer attributes in each layer and attribute description rules of each layer attribute according to multiple layers in the preset intelligent system architecture framework information.

[0238] S602, determining each modeling attribute according to the system requirement document and each layer attribute.

[0239] According to the system requirement document, the implementation functions, application fields and application modes of the target intelligent complex system are obtained; according to the implementation functions, application fields and application modes, the business requirement decomposition attributes, capability classification attributes and required resource attributes in each layer attribute are determined as each modeling attribute.

[0240] S603: Determine attribute description information of each modeling attribute based on the attribute description rules of each modeling attribute and each layer attribute.

[0241] S604: Determine the initial intelligent system architecture of the target intelligent complex system according to each modeling attribute and each attribute description information.

[0242] S605, verify the data completeness of the initial intelligent system architecture to obtain a candidate intelligent system architecture.

[0243] Modeling and simulating the initial intelligent system architecture to obtain a virtual intelligent complex system corresponding to the initial intelligent system architecture; running the virtual intelligent complex system; if the virtual intelligent complex system runs normally, determining the initial intelligent system architecture as a candidate intelligent system architecture.

[0244] S606: Perform data consistency verification on the candidate intelligent system architecture according to each modeling attribute and each attribute description information to obtain the intelligent system architecture.

[0245] According to the description information of each attribute, data consistency verification is performed on the modeling attributes within the same layer and the modeling attributes associated between different layers; if the key information in the modeling attributes within the same layer is consistent, and the key information of the modeling attributes associated between different layers is consistent, the candidate intelligent system architecture is determined to be the intelligent system architecture; if there is inconsistent information in the key information in the modeling attributes within the same layer and the key information of the modeling attributes associated between different layers, the description information of each attribute is adjusted, and the intelligent system architecture is determined based on the adjusted attribute description information.

[0246] S607, obtaining system construction data corresponding to each attribute description information.

[0247] S608, fill the system construction data into the corresponding position of the intelligent system architecture to obtain the target intelligent complex system.

[0248] The above process of S601-S608 can refer to the description of the above method embodiment, and its implementation principle and technical effect are similar, which will not be repeated here.

[0249] It should be understood that, although the various steps in the flowcharts involved in the above-mentioned embodiments are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence according to the order indicated by the arrows. Unless there is a clear explanation in this article, the execution of these steps does not have a strict order restriction, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above-mentioned embodiments can include multiple steps or multiple stages, and these steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a part of the steps or stages in other steps.

[0250] Based on the same inventive concept, the embodiment of the present application also provides an intelligent complex system construction device for implementing the intelligent complex system construction method involved above. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme recorded in the above method, so the specific limitations in one or more embodiments of the intelligent complex system construction device provided below can refer to the limitations of the intelligent complex system construction method above, and will not be repeated here.

[0251] In an exemplary embodiment, as shown in FIG34 , an intelligent complex system construction device 1 is provided, comprising: an attribute information determination module 10, a system architecture determination module 20 and an intelligent system construction module 30, wherein:

[0252] The attribute information determination module 10 is used to respond to the construction request of the target intelligent complex system and determine multiple modeling attributes of the target intelligent complex system and attribute description information of each modeling attribute according to the system requirement document; the attribute description information includes multiple subtasks of at least one system task, capability information required for each subtask and system support resources.

[0253] The system architecture determination module 20 is used to determine the intelligent system architecture of the target intelligent complex system according to each modeling attribute and each attribute description information.

[0254] The intelligent system construction module 30 is used to construct a target intelligent complex system based on the intelligent system architecture.

[0255] In one embodiment, the attribute information determination module 10 is further used to:

[0256] According to multiple layers in the preset intelligent system architecture framework information, multiple layer attributes in each layer and attribute description rules of each layer attribute are obtained; according to the system requirement document and each layer attribute, each modeling attribute is determined; based on each modeling attribute and the attribute description rules of each layer attribute, attribute description information of each modeling attribute is determined.

[0257] In one embodiment, the attribute information determination module 10 is further used to:

[0258] According to the system requirement document, the implementation functions, application fields and application modes of the target intelligent complex system are obtained; according to the implementation functions, application fields and application modes, the business requirement decomposition attributes, capability classification attributes and required resource attributes in each layer attribute are determined as each modeling attribute.

[0259] In one embodiment, the attribute information determination module 10 is further used to:

[0260] According to the attribute description rules of each layer attribute, the attribute description rules of the business requirement decomposition attributes, the attribute description rules of the capability classification attributes and the attribute description rules of the required resource attributes are obtained; according to the system requirement document and the attribute description rules of the business requirement decomposition attributes, the attribute description information of the business requirement decomposition attributes is determined; according to the attribute description rules of the capability classification attributes, the attribute description information of the capability classification attributes is determined; according to the attribute description rules of the required resource attributes, the attribute description information of the required resource attributes is determined.

[0261] In one embodiment, the attribute information determination module 10 is further used to:

[0262] The system tasks of the target intelligent complex system in the system requirement document are decomposed to obtain multiple subtasks of the target intelligent complex system; each subtask is described according to the attribute description rule of the business requirement decomposition attribute to obtain subtask description information; and the subtask description information is used as the attribute description information of the business requirement decomposition attribute.

[0263] In one embodiment, the attribute information determination module 10 is further used to:

[0264] According to the task capability knowledge base and multiple subtasks of the target intelligent complex system, the system capability of the target intelligent complex system is decomposed to obtain multiple sub-capabilities of the target intelligent complex system; according to the attribute description rules of the capability classification attributes, each sub-capability is described to obtain sub-capability description information; the sub-capability description information is used as the attribute description information of the capability classification attributes.

[0265] In one embodiment, the attribute information determination module 10 is further used to:

[0266] According to the capability resource knowledge base and multiple sub-capabilities of the target intelligent complex system, the system support resources of the target intelligent complex system are determined; according to the attribute description rules of the essential resource attributes, the system support resources are described to obtain resource description information; the resource description information is determined as the attribute description information of the essential resource attributes.

[0267] In one embodiment, the system architecture determination module 20 is further used to:

[0268] According to each modeling attribute and each attribute description information, the initial intelligent system architecture of the target intelligent complex system is determined; the initial intelligent system architecture is verified to obtain the intelligent system architecture.

[0269] In one embodiment, the system architecture determination module 20 is further used to:

[0270] The data completeness of the initial intelligent system architecture is verified to obtain the candidate intelligent system architecture; according to each modeling attribute and each attribute description information, the data consistency of the candidate intelligent system architecture is verified to obtain the intelligent system architecture.

[0271] In one embodiment, the system architecture determination module 20 is further used to:

[0272] Modeling and simulating the initial intelligent system architecture to obtain a virtual intelligent complex system corresponding to the initial intelligent system architecture; running the virtual intelligent complex system; if the virtual intelligent complex system runs normally, determining the initial intelligent system architecture as a candidate intelligent system architecture.

[0273] In one embodiment, the system architecture determination module 20 is further used to:

[0274] If the virtual intelligent complex system operates abnormally, the virtual intelligent complex system is adjusted; an initial intelligent system architecture adjusted synchronously with the virtual intelligent complex system is obtained; and the adjusted initial intelligent system architecture is determined as a candidate intelligent system architecture.

[0275] In one embodiment, the system architecture determination module 20 is further used to:

[0276] According to the description information of each attribute, data consistency verification is performed on the modeling attributes within the same layer and the modeling attributes associated between different layers; if the key information in the modeling attributes within the same layer is consistent, and the key information of the modeling attributes associated between different layers is consistent, the candidate intelligent system architecture is determined to be the intelligent system architecture; if there is inconsistent information in the key information in the modeling attributes within the same layer and the key information of the modeling attributes associated between different layers, the description information of each attribute is adjusted, and the intelligent system architecture is determined based on the adjusted attribute description information.

[0277] In one embodiment, the intelligent system building module 30 is further used for:

[0278] Obtain system construction data corresponding to each attribute description information; fill the system construction data in the corresponding position of the intelligent system architecture to obtain the target intelligent complex system.

[0279] Each module in the above-mentioned intelligent complex system construction device can be implemented in whole or in part by software, hardware and their combination. Each of the above-mentioned modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory in the computer device in the form of software, so that the processor can call and execute the operations corresponding to each of the above modules.

[0280] In an exemplary embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and when the processor executes the computer program, the following steps are implemented:

[0281] In response to a request to build a target intelligent complex system, multiple modeling attributes of the target intelligent complex system and attribute description information of each modeling attribute are determined according to a system requirement document; the attribute description information includes multiple subtasks of at least one system task, capability information required for each subtask, and system support resources;

[0282] Determine the intelligent system architecture of the target intelligent complex system based on each modeling attribute and each attribute description information;

[0283] Build the target intelligent complex system based on the intelligent system architecture.

[0284] The implementation principles and technical effects of each step implemented by the processor in the embodiment of the present application are similar to the principles of the above-mentioned intelligent complex system construction method, and will not be repeated here.

[0285] In one embodiment, a computer readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, the following steps are implemented:

[0286] In response to a request to build a target intelligent complex system, multiple modeling attributes of the target intelligent complex system and attribute description information of each modeling attribute are determined according to a system requirement document; the attribute description information includes multiple subtasks of at least one system task, capability information required for each subtask, and system support resources;

[0287] Determine the intelligent system architecture of the target intelligent complex system based on each modeling attribute and each attribute description information;

[0288] Build the target intelligent complex system based on the intelligent system architecture.

[0289] The implementation principles and technical effects of the various steps implemented when the computer program in the embodiment of the present application is executed by the processor are similar to the principles of the above-mentioned intelligent complex system construction method, and will not be repeated here.

[0290] In one embodiment, a computer program product is provided, comprising a computer program, which, when executed by a processor, implements the following steps:

[0291] In response to a request to build a target intelligent complex system, multiple modeling attributes of the target intelligent complex system and attribute description information of each modeling attribute are determined according to a system requirement document; the attribute description information includes multiple subtasks of at least one system task, capability information required for each subtask, and system support resources;

[0292] Determine the intelligent system architecture of the target intelligent complex system based on each modeling attribute and each attribute description information;

[0293] Build the target intelligent complex system based on the intelligent system architecture.

[0294] The implementation principles and technical effects of the various steps implemented when the computer program in the embodiment of the present application is executed by the processor are similar to the principles of the above-mentioned intelligent complex system construction method, and will not be repeated here.

[0295] It should be noted that the personnel information (including but not limited to personnel equipment information, personnel personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the personnel or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant regulations.

[0296] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. Non-relational databases may include distributed databases based on blockchains, etc., but are not limited to this. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., but are not limited to this.

[0297] The technical features of the above embodiments may be arbitrarily combined. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0298] The above-described embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.

Claims

1. A method for constructing an intelligent complex system, characterized in that: The method comprises: In response to a construction request of a target intelligent complex system of a target park, obtaining, according to multiple layers in preset intelligent system architecture framework information, multiple layer attributes in each layer and attribute description rules of each layer attribute; According to the system requirement document of the target park, the layer attributes and the attribute description rules of the layer attributes, multiple park modeling attributes of the target intelligent complex system and the attribute description information of each park modeling attribute are determined; the attribute description information includes multiple subtasks of at least one system task of the target park, the capability information required for each subtask and the system support resources; Determine the intelligent system architecture of the target intelligent complex system according to the modeling attributes of each park and the attribute description information; Acquire system construction data corresponding to each of the attribute description information; the system construction data refers to task data of each of the subtasks in each of the attribute description information, capability information required by each of the subtasks, and resource data of the system support resources; Fill each of the system construction data into the corresponding position of the intelligent system architecture to obtain the target intelligent complex system.

2. The method according to claim 1, characterized in that: Determining multiple park modeling attributes of the target intelligent complex system and attribute description information of each park modeling attribute according to the system requirement document of the target park, each layer attribute and attribute description rules of each layer attribute includes: Determine the modeling attributes of each of the parks according to the system requirement document and the attributes of each of the layers; Based on the attribute description rules of each of the park modeling attributes and each of the layer attributes, attribute description information of each of the park modeling attributes is determined.

3. The method according to claim 2, characterized in that Determining the modeling attributes of each park according to the system requirement document and the attributes of each layer includes: According to the system requirement document, obtain the realization functions, application fields and application modes of the target intelligent complex system; According to the implementation function, the application field and the application mode, the business requirement decomposition attribute, the capability classification attribute and the necessary resource attribute in each of the layer attributes are determined as the modeling attributes of each of the parks.

4. The method according to claim 2, characterized in that: Each of the park modeling attributes includes a business requirement decomposition attribute, a capability classification attribute, and a required resource attribute; the attribute description information of each of the park modeling attributes is determined based on the attribute description rules of each of the park modeling attributes and each of the layer attributes, including: According to the attribute description rules of each of the layer attributes, the attribute description rules of the business requirement decomposition attribute, the attribute description rules of the capability classification attribute and the attribute description rules of the essential resource attribute are obtained; Determine attribute description information of the business requirement decomposition attribute according to the system requirement document and the attribute description rule of the business requirement decomposition attribute; Determining attribute description information of the capability classification attribute according to the attribute description rule of the capability classification attribute; According to the attribute description rule of the essential resource attribute, the attribute description information of the essential resource attribute is determined.

5. The method according to claim 4, characterized in that The determining the attribute description information of the business requirement decomposition attribute according to the system requirement document and the attribute description rule of the business requirement decomposition attribute includes: Decomposing the system tasks of the target intelligent complex system in the system requirement document to obtain a plurality of subtasks of the target intelligent complex system; Describing each of the subtasks according to the attribute description rule of the business requirement decomposition attribute to obtain subtask description information; The subtask description information is used as the attribute description information of the business requirement decomposition attribute.

6. The method according to claim 4, characterized in that The determining the attribute description information of the capability classification attribute according to the attribute description rule of the capability classification attribute includes: Decomposing the system capability of the target intelligent complex system according to the task capability knowledge base and the multiple subtasks of the target intelligent complex system to obtain the multiple subcapabilities of the target intelligent complex system; Describing each of the sub-capabilities according to the attribute description rule of the capability classification attribute to obtain sub-capability description information; The sub-capability description information is used as the attribute description information of the capability classification attribute.

7. The method according to claim 4, characterized in that The determining the attribute description information of the essential resource attribute according to the attribute description rule of the essential resource attribute includes: Determining system support resources of the target intelligent complex system according to a capability resource knowledge base and a plurality of sub-capabilities of the target intelligent complex system; Describing the system support resources according to the attribute description rules of the essential resource attributes to obtain resource description information; The resource description information is determined as the attribute description information of the essential resource attribute.

8. The method according to any one of claims 1 to 7, characterized in that: Determining the intelligent system architecture of the target intelligent complex system according to the modeling attributes of each park and the attribute description information includes: Determine the initial intelligent system architecture of the target intelligent complex system according to the modeling attributes of each park and the attribute description information; The initial intelligent system architecture is verified to obtain the intelligent system architecture.

9. The method according to claim 8, characterized in that The verifying the initial intelligent system architecture to obtain the intelligent system architecture includes: Performing data completeness verification on the initial intelligent system architecture to obtain a candidate intelligent system architecture; According to each of the park modeling attributes and each of the attribute description information, data consistency verification is performed on the candidate intelligent system architecture to obtain the intelligent system architecture.

10. The method according to claim 9, characterized in that The data completeness verification of the initial intelligent system architecture to obtain a candidate intelligent system architecture includes: Modeling and simulating the initial intelligent system architecture to obtain a virtual intelligent complex system corresponding to the initial intelligent system architecture; Running the virtual intelligent complex system; If the virtual intelligent complex system operates normally, the initial intelligent system architecture is determined as the candidate intelligent system architecture.

11. The method according to claim 10, characterized in that The method further comprises: If the virtual intelligent complex system operates abnormally, adjusting the virtual intelligent complex system; Acquire an initial intelligent system architecture that is adjusted synchronously with the virtual intelligent complex system; The adjusted initial intelligent system architecture is determined as the candidate intelligent system architecture.

12. The method according to claim 9, characterized in that The step of performing data consistency verification on the candidate intelligent system architecture according to each of the park modeling attributes and each of the attribute description information to obtain the intelligent system architecture includes: According to each of the attribute description information, data consistency check is performed on the park modeling attributes in the same layer and the park modeling attributes associated between different layers; If the key information in the park modeling attributes in the same layer is consistent, and the key information in the park modeling attributes associated between different layers is consistent, then the candidate intelligent system architecture is determined to be the intelligent system architecture; If there is inconsistent information between the key information in the park modeling attributes within the same layer and the key information in the park modeling attributes associated between different layers, the attribute description information is adjusted, and the intelligent system architecture is determined based on the adjusted attribute description information.

13. An intelligent complex system construction device, characterized in that: The device comprises: An attribute information determination module is used to respond to a construction request of a target intelligent complex system of a target park, and obtain multiple layer attributes in each layer and attribute description rules of each layer attribute according to multiple layers in the preset intelligent system architecture framework information; determine multiple park modeling attributes of the target intelligent complex system and attribute description information of each park modeling attribute according to the system requirement document of the target park, each layer attribute and attribute description rules of each layer attribute; the attribute description information includes multiple subtasks of at least one system task of the target park, capability information required for each subtask and system support resources; A system architecture determination module, used to determine the intelligent system architecture of the target intelligent complex system according to the modeling attributes of each park and the attribute description information; An intelligent system construction module is used to obtain system construction data corresponding to each of the attribute description information; the system construction data refers to the task data of each of the subtasks in the attribute description information, the capability information required for each of the subtasks and the resource data of the system support resources; each of the system construction data is filled in the corresponding position of the intelligent system architecture to obtain the target intelligent complex system.

14. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 12 are implemented.

15. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 12 are implemented.

16. A computer program product comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 12 are implemented.

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