Hydroelectric knowledge reasoning-oriented search engine construction method, system, storage medium and device

Abstract

The invention provides a hydroelectric knowledge reasoning-oriented search engine construction method, system, storage medium and device, and belongs to the field of hydroelectric knowledge processing. The method comprises the following steps: collecting scene information of hydroelectric knowledge reasoning and a first search engine model; activating a forward reasoning port according to the scene information, and inputting retrieval request data into the forward reasoning port to obtain a retrieval intermediate quantity; generating retrieval conclusion data according to the retrieval intermediate quantity and the first search engine model; and inputting the retrieval conclusion data into a backward reasoning port to generate a second search engine model. The technical problem that in the prior art, an index or a search engine is usually constructed only through a single or fixed-mode reasoning mode in the knowledge reasoning process, and the requirement for high-speed operation efficiency when a large amount of hydropower operation data appear cannot be met is solved.

Description

Technical Field

[0001] This invention relates to the field of hydropower knowledge processing, specifically to a method, system, storage medium, and device for constructing a search engine for hydropower knowledge reasoning. Background Technology

[0002] With the continuous development of intelligent technology, people are using more and more intelligent devices in their lives, work, and study. The use of intelligent technology has improved people's quality of life and increased their learning and work efficiency.

[0003] Currently, in the reasoning process of hydropower knowledge graphs, fixed patterns are typically used to transform the knowledge reasoning process in order to build a search engine that facilitates querying various element parameters within the knowledge graph. However, existing technologies often rely on a single or fixed reasoning method to build indexes or search engines, which cannot meet the high-speed operation requirements when dealing with large amounts of hydropower operation data. No effective solution has yet been proposed to address these issues. Summary of the Invention

[0004] The main objective of this invention is to provide a method and system for constructing a search engine for hydropower knowledge reasoning, so as to at least solve the technical problem that the existing knowledge reasoning process often only uses a single or fixed reasoning method to construct indexes or search engines, which cannot meet the requirements of high-speed operation efficiency when a large amount of hydropower operation data appears.

[0005] To achieve the above-mentioned technical features, the objective of this invention is as follows: a method for constructing a search engine for hydropower knowledge reasoning, comprising: Collect scenario information and the first search engine model for hydropower knowledge reasoning; The forward inference port is activated based on the scenario information, and the retrieval request data is input into the forward inference port to obtain the retrieval intermediate quantity; Based on the retrieval intermediate values ​​and the first search engine model, retrieval conclusion data is generated; The search results data are input into the backward inference port to generate a second search engine model.

[0006] Preferably, before collecting the scenario information for hydropower knowledge reasoning and the first search engine model, the method further includes: Retrieve historical input and output data; The first search engine model is constructed based on the preset model algorithm and the historical input and output data.

[0007] Preferably, the step of activating the forward inference port based on the scene information and inputting the retrieval request data into the forward inference port to obtain the retrieval intermediate quantity includes: The request module and the water and electricity scene module were extracted from the scene information; The request module and the hydropower scenario module are fitted together, and the resulting dataset is used as the retrieval request data; The retrieval request data is processed using the forward inference port to obtain the retrieval intermediate quantity.

[0008] Preferably, the step of inputting the retrieval conclusion data into the backward inference port to generate the second search engine model includes: Obtain the backward inference port; The retrieval conclusion data is input into the backward inference port, and the backward inference output port data is collected as verification data. The verification data and the retrieval conclusion data are compared and verified to obtain the verification results. When the verification result is valid, the second search engine model is constructed.

[0009] Another aspect of the present invention provides a search engine construction system for hydropower knowledge reasoning, the system being used to implement the method, the system comprising: The data acquisition module is used to collect scenario information and the first search engine model for hydropower knowledge reasoning. The activation module is used to activate the forward inference port according to the scene information and input the retrieval request data into the forward inference port to obtain the retrieval intermediate quantity; The generation module is used to generate retrieval conclusion data based on the retrieval intermediate data and the first search engine model; The input module is used to input the retrieval result data into the backward inference port to generate a second search engine model.

[0010] Preferably, the system further includes: The acquisition module is used to acquire historical input and output data; The construction module is used to construct the first search engine model based on the preset model algorithm and the historical input and output data.

[0011] Preferably, the activation module includes: The extraction unit is used to extract the request module and the water and electricity scene module from the scene information; The fitting unit is used to fit the request module and the hydropower scenario module, and the resulting dataset is used as the retrieval request data. The processing unit is used to process the retrieval request data using the forward inference port to obtain the retrieval intermediate quantity.

[0012] Preferably, the input module includes: Acquisition unit, used to acquire the backward inference port; The backward inference unit is used to input the retrieval conclusion data into the backward inference port and collect the backward inference output port data as verification data. The comparison unit is used to compare the verification data and the retrieval conclusion data to obtain the verification result. A construction unit is used to construct the second search engine model when the verification result is valid.

[0013] In another aspect, the present invention provides a non-volatile storage medium comprising a stored program, wherein the program, when executed, controls the device on which the non-volatile storage medium resides to perform the method described thereon.

[0014] In another aspect, the present invention provides an electronic device comprising a processor and a memory; the memory stores computer-readable instructions, and the processor is configured to execute the computer-readable instructions, wherein the computer-readable instructions, when executed, perform the method described herein.

[0015] The present invention has the following beneficial effects: In this embodiment of the invention, the following approach is adopted: Scene information for hydropower knowledge reasoning and a first search engine model are collected; a forward inference port is activated based on the scene information, and retrieval request data is input into the forward inference port to obtain intermediate retrieval data; retrieval conclusion data is generated based on the intermediate retrieval data and the first search engine model; and the retrieval conclusion data is input into the backward inference port to generate a second search engine model. This approach solves the technical problem in the prior art where knowledge reasoning processes often rely solely on a single or fixed-pattern reasoning method to construct indexes or search engines, failing to meet the high-speed operation efficiency requirements when a large amount of hydropower operation data is available. Attached Figure Description

[0016] The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0017] Figure 1 This is a flowchart of a search engine construction method for hydropower knowledge reasoning according to an embodiment of the present invention.

[0018] Figure 2 This is a structural block diagram of a search engine construction system for hydropower knowledge reasoning according to an embodiment of the present invention.

[0019] Figure 3This is a block diagram of a terminal device for performing the method according to an embodiment of the present invention.

[0020] Figure 4 It is a storage unit according to an embodiment of the present invention for holding or carrying program code that implements the method according to the present invention. Detailed Implementation

[0021] The embodiments of the present invention will be further described below with reference to the accompanying drawings.

[0022] The technical solution of the present invention will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0023] According to an embodiment of the present invention, a method embodiment for constructing a search engine for hydropower knowledge reasoning is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0024] Example 1: Figure 1 This is a flowchart of a search engine construction method for hydropower knowledge reasoning according to an embodiment of the present invention, such as... Figure 1 As shown, the method includes the following steps: Step S102: Collect scenario information and the first search engine model for hydropower knowledge reasoning.

[0025] Step S104: Activate the forward inference port according to the scene information, and input the retrieval request data into the forward inference port to obtain the retrieval intermediate quantity.

[0026] Step S106: Generate retrieval conclusion data based on the retrieval intermediate data and the first search engine model.

[0027] Step S108: Input the search result data into the backward inference port to generate the second search engine model.

[0028] Optionally, before collecting the scenario information for hydropower knowledge reasoning and the first search engine model, the method further includes: acquiring historical input data and output data; and constructing the first search engine model based on a preset model algorithm and the historical input data and output data.

[0029] Optionally, activating the forward inference port based on the scene information and inputting the retrieval request data into the forward inference port to obtain the retrieval intermediate quantity includes: extracting the request module and the hydropower scene module from the scene information; fitting the request module and the hydropower scene module to generate a dataset as the retrieval request data; and processing the retrieval request data using the forward inference port to obtain the retrieval intermediate quantity.

[0030] Optionally, the step of inputting the retrieval conclusion data into the backward inference port to generate the second search engine model includes: obtaining the backward inference port; inputting the retrieval conclusion data into the backward inference port and collecting backward inference output port data as verification data; verifying and comparing the verification data and the retrieval conclusion data to obtain a verification result; and constructing the second search engine model when the verification result is valid.

[0031] The above embodiments solve the technical problem that the existing technology often uses only a single or fixed reasoning method to build indexes or search engines for knowledge reasoning processes, which cannot meet the requirements of high-speed operation efficiency when a large amount of hydropower operation data appears.

[0032] Example 2: Figure 2 This is a structural block diagram of a search engine construction system for hydropower knowledge reasoning according to an embodiment of the present invention, such as... Figure 2 As shown, the system includes: The data acquisition module 20 is used to collect scene information and the first search engine model for hydropower knowledge reasoning.

[0033] The activation module 22 is used to activate the forward inference port according to the scene information and input the retrieval request data into the forward inference port to obtain the retrieval intermediate quantity.

[0034] The generation module 24 is used to generate retrieval conclusion data based on the retrieval intermediate data and the first search engine model.

[0035] Input module 26 is used to input the retrieval conclusion data to the backward inference port to generate a second search engine model.

[0036] Optionally, the system further includes: an acquisition module for acquiring historical input data and output data; and a construction module for constructing the first search engine model based on a preset model algorithm and the historical input data and output data.

[0037] Optionally, the activation module includes: an extraction unit for extracting the request module and the hydropower scene module from the scene information; a fitting unit for fitting the request module and the hydropower scene module to generate a dataset as the retrieval request data; and a processing unit for processing the retrieval request data using the forward inference port to obtain the retrieval intermediate quantity.

[0038] Optionally, the input module includes: an acquisition unit for acquiring the backward inference port; a backward inference unit for inputting the retrieval conclusion data into the backward inference port and collecting backward inference output port data as verification data; a comparison unit for comparing the verification data and the retrieval conclusion data to obtain a verification result; and a construction unit for constructing the second search engine model when the verification result is valid.

[0039] The above embodiments solve the technical problem that the existing technology often uses only a single or fixed reasoning method to build indexes or search engines for knowledge reasoning processes, which cannot meet the requirements of high-speed operation efficiency when a large amount of hydropower operation data appears.

[0040] According to another aspect of the present invention, a non-volatile storage medium is also provided, the non-volatile storage medium including a stored program, wherein the program, when running, controls the device where the non-volatile storage medium is located to execute a search engine construction method for hydropower knowledge reasoning.

[0041] Specifically, the above method includes: collecting scenario information and a first search engine model for hydropower knowledge reasoning; activating the forward inference port based on the scenario information and inputting retrieval request data into the forward inference port to obtain retrieval intermediate data; generating retrieval conclusion data based on the retrieval intermediate data and the first search engine model; and inputting the retrieval conclusion data into the backward inference port to generate a second search engine model. Optionally, before collecting the scenario information and the first search engine model for hydropower knowledge reasoning, the method further includes: acquiring historical input data and output data; and constructing the first search engine model based on a preset model algorithm and the historical input data and output data. Optionally, activating the forward inference port based on the scenario information and inputting retrieval request data into the forward inference port to obtain retrieval intermediate data includes: extracting the request module and the hydropower scenario module from the scenario information; fitting the request module and the hydropower scenario module to generate a dataset as the retrieval request data; and processing the retrieval request data using the forward inference port to obtain the retrieval intermediate data. Optionally, the step of inputting the retrieval conclusion data into the backward inference port to generate the second search engine model includes: obtaining the backward inference port; inputting the retrieval conclusion data into the backward inference port and collecting backward inference output port data as verification data; verifying and comparing the verification data and the retrieval conclusion data to obtain a verification result; and constructing the second search engine model when the verification result is valid.

[0042] According to another aspect of the present invention, an electronic device is also provided, comprising a processor and a memory; the memory stores computer-readable instructions, and the processor is configured to execute the computer-readable instructions, wherein the computer-readable instructions, when executed, perform a search engine construction method for hydropower knowledge reasoning.

[0043] Specifically, the above method includes: collecting scenario information and a first search engine model for hydropower knowledge reasoning; activating the forward inference port based on the scenario information and inputting retrieval request data into the forward inference port to obtain retrieval intermediate data; generating retrieval conclusion data based on the retrieval intermediate data and the first search engine model; and inputting the retrieval conclusion data into the backward inference port to generate a second search engine model. Optionally, before collecting the scenario information and the first search engine model for hydropower knowledge reasoning, the method further includes: acquiring historical input data and output data; and constructing the first search engine model based on a preset model algorithm and the historical input data and output data. Optionally, activating the forward inference port based on the scenario information and inputting retrieval request data into the forward inference port to obtain retrieval intermediate data includes: extracting the request module and the hydropower scenario module from the scenario information; fitting the request module and the hydropower scenario module to generate a dataset as the retrieval request data; and processing the retrieval request data using the forward inference port to obtain the retrieval intermediate data. Optionally, the step of inputting the retrieval conclusion data into the backward inference port to generate the second search engine model includes: obtaining the backward inference port; inputting the retrieval conclusion data into the backward inference port and collecting backward inference output port data as verification data; verifying and comparing the verification data and the retrieval conclusion data to obtain a verification result; and constructing the second search engine model when the verification result is valid.

[0044] The sequence numbers of the above embodiments of the present invention are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0045] In the above embodiments of the present invention, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0046] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. The device embodiments described above are merely illustrative; for example, the division of units can be a logical functional division, and in actual implementation, there may be other division methods. For instance, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the displayed or discussed mutual coupling, direct coupling, or communication connection may be through some interfaces; the indirect coupling or communication connection between units or modules may be electrical or other forms.

[0047] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0048] in addition, Figure 3 This is a schematic diagram of the hardware structure of a terminal device provided in an embodiment of this application. Figure 3 As shown, the terminal device may include an input device 30, a processor 31, an output device 32, a memory 33, and at least one communication bus 34. The communication bus 34 is used to realize communication connections between components. The memory 33 may include high-speed RAM memory, and may also include non-volatile memory (NVM), such as at least one disk storage device. The memory 33 may store various programs for performing various processing functions and implementing the method steps of this embodiment.

[0049] Optionally, the processor 31 may be implemented as a central processing unit (CPU), application-specific integrated circuit (ASIC), digital signal processor (DSP), digital signal processing device (DSPD), programmable logic device (PLD), field-programmable gate array (FPGA), controller, microcontroller, microprocessor or other electronic components. The processor 31 is coupled to the input device 30 and output device 32 via wired or wireless connection.

[0050] Optionally, the input device 30 may include various input devices, such as a user interface, a device interface, a programmable software interface, a camera, and a sensor. Optionally, the device interface may be a wired interface for data transmission between devices, or a hardware interface (e.g., USB interface, serial port) for data transmission between devices. Optionally, the user interface may be a user-facing control button, a voice input device for receiving voice input, or a touch-sensing device for receiving user touch input (e.g., a touchscreen, touchpad). Optionally, the programmable software interface may be an entry point for users to edit or modify programs, such as a chip's input pin interface or input interface. Optionally, the transceiver may be a radio frequency transceiver chip with communication functions, a baseband processing chip, and a transceiver antenna. Audio input devices such as microphones can receive voice data. Output device 32 may include displays, speakers, and other output devices.

[0051] In this embodiment, the processor of the terminal device includes functions for executing the modules of the data processing device in each device. The specific functions and technical effects can be referred to in the above embodiments, and will not be repeated here.

[0052] Figure 4 This is a schematic diagram of the hardware structure of a terminal device provided in another embodiment of this application. Figure 4 Yes Figure 3 A specific implementation example in the implementation process. For example... Figure 4 As shown, the terminal device in this embodiment includes a processor 41 and a memory 42.

[0053] The processor 41 executes the computer program code stored in the memory 42 to implement the method in the above embodiments.

[0054] Memory 42 is configured to store various types of data to support operation on the terminal device. Examples of this data include instructions for any application or method operating on the terminal device, such as messages, pictures, videos, etc. Memory 42 may include random access memory (RAM) and may also include non-volatile memory, such as at least one disk storage device.

[0055] Optionally, the processor 41 is located in the processing component 40. The terminal device may also include: a communication component 43, a power supply component 44, a multimedia component 45, an audio component 46, an input / output interface 47, and / or a sensor component 48. The specific components included in the terminal device are determined according to actual needs, and this embodiment does not limit this.

[0056] Processing component 40 typically controls the overall operation of the terminal device. Processing component 40 may include one or more processors 41 to execute instructions to complete all or part of the steps of the above-described method. Furthermore, processing component 40 may include one or more modules to facilitate interaction between processing component 40 and other components. For example, processing component 40 may include a multimedia module to facilitate interaction between multimedia component 45 and processing component 40.

[0057] Power supply component 44 provides power to various components of the terminal device. Power supply component 44 may include a power management system, one or more power supplies, and other components associated with generating, managing, and distributing power to the terminal device.

[0058] Multimedia component 45 includes a display screen that provides an output interface between a terminal device and a user. In some embodiments, the display screen may include a liquid crystal display (LCD) and a touch panel (TP). If the display screen includes a touch panel, the display screen may be implemented as a touchscreen to receive input signals from the user. The touch panel includes one or more touch sensors to sense touches, swipes, and gestures on the touch panel. The touch sensors may sense not only the boundaries of the touch or swipe action but also the duration and pressure associated with the touch or swipe operation.

[0059] Audio component 46 is configured to output and / or input audio signals. For example, audio component 46 includes a microphone (MIC) configured to receive external audio signals when the terminal device is in an operating mode, such as a voice recognition mode. The received audio signals may be further stored in memory 42 or transmitted via communication component 43. In some embodiments, audio component 46 also includes a speaker for outputting audio signals.

[0060] Input / output interface 47 provides an interface between processing component 40 and peripheral interface modules, such as click wheels, buttons, etc. These buttons may include, but are not limited to, volume buttons, start buttons, and lock buttons.

[0061] Sensor assembly 48 includes one or more sensors for providing status assessments of various aspects of the terminal device. For example, sensor assembly 48 can detect the on / off state of the terminal device, the relative positioning of components, and the presence or absence of user contact with the terminal device. Sensor assembly 48 may include a proximity sensor configured to detect the presence of nearby objects without any physical contact, including detecting the distance between the user and the terminal device. In some embodiments, sensor assembly 48 may also include a camera, etc.

[0062] Communication component 43 is configured to facilitate wired or wireless communication between the terminal device and other devices. The terminal device can access wireless networks based on communication standards, such as WiFi, 2G, or 3G, or combinations thereof. In one embodiment, the terminal device may include a SIM card slot for inserting a SIM card, enabling the terminal device to log in to a GPRS network and establish communication with a server via the Internet.

[0063] As can be seen from the above, in Figure 4 The communication component 43, audio component 46, input / output interface 47, and sensor component 48 involved in the embodiment can all be used as... Figure 3 The implementation method of the input device in the embodiment.

[0064] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. The device embodiments described above are merely illustrative; for example, the division of units can be a logical functional division, and in actual implementation, there may be other division methods. For instance, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the displayed or discussed mutual coupling, direct coupling, or communication connection may be through some interfaces; the indirect coupling or communication connection between units or modules may be electrical or other forms.

[0065] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0066] Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0067] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, read-only memory (ROM), random access memory (RAM), portable hard drives, magnetic disks, or optical disks.

[0068] The present invention and its embodiments have been described above. This description is not restrictive. The accompanying drawings are only one embodiment of the present invention. The actual structure is not limited to this. In short, if a person skilled in the art is inspired by this description and designs a similar structure and embodiment without departing from the spirit of the present invention, such design should fall within the protection scope of the present invention.

Claims

1. A method for constructing a search engine for hydropower knowledge reasoning, characterized in that, include: Collect scenario information and the first search engine model for hydropower knowledge reasoning; The forward inference port is activated based on the scenario information, and the retrieval request data is input into the forward inference port to obtain the retrieval intermediate quantity; Based on the retrieval intermediate values ​​and the first search engine model, retrieval conclusion data is generated; The search results data are input into the backward inference port to generate a second search engine model.

2. The method for constructing a search engine for hydropower knowledge reasoning according to claim 1, characterized in that, Before collecting the scenario information for hydropower knowledge reasoning and the first search engine model, the method further includes: Retrieve historical input and output data; The first search engine model is constructed based on the preset model algorithm and the historical input and output data.

3. The method for constructing a search engine for hydropower knowledge reasoning according to claim 1, characterized in that, The step of activating the forward inference port based on the scene information and inputting the retrieval request data into the forward inference port to obtain the retrieval intermediate quantity includes: The request module and the water and electricity scene module were extracted from the scene information; The request module and the hydropower scenario module are fitted together, and the resulting dataset is used as the retrieval request data; The retrieval request data is processed using the forward inference port to obtain the retrieval intermediate quantity.

4. The method for constructing a search engine for hydropower knowledge reasoning according to claim 1, characterized in that, The step of inputting the retrieval result data into the backward inference port to generate the second search engine model includes: Obtain the backward inference port; The retrieval conclusion data is input into the backward inference port, and the backward inference output port data is collected as verification data. The verification data and the retrieval conclusion data are compared and verified to obtain the verification results. When the verification result is valid, the second search engine model is constructed.

5. A search engine construction system for hydropower knowledge reasoning, the system being used to implement the method described in any one of claims 1-4, characterized in that, The system includes: The data acquisition module is used to collect scenario information and the first search engine model for hydropower knowledge reasoning. The activation module is used to activate the forward inference port according to the scene information and input the retrieval request data into the forward inference port to obtain the retrieval intermediate quantity; The generation module is used to generate retrieval conclusion data based on the retrieval intermediate data and the first search engine model; The input module is used to input the retrieval result data into the backward inference port to generate a second search engine model.

6. The search engine construction system for hydropower knowledge reasoning according to claim 5, characterized in that, The system also includes: The acquisition module is used to acquire historical input and output data; The construction module is used to construct the first search engine model based on the preset model algorithm and the historical input and output data.

7. The search engine construction system for hydropower knowledge reasoning according to claim 5, characterized in that, The activation module includes: The extraction unit is used to extract the request module and the water and electricity scene module from the scene information; The fitting unit is used to fit the request module and the hydropower scenario module, and the resulting dataset is used as the retrieval request data. The processing unit is used to process the retrieval request data using the forward inference port to obtain the retrieval intermediate quantity.

8. The search engine construction system for hydropower knowledge reasoning according to claim 5, characterized in that, The input module includes: Acquisition unit, used to acquire the backward inference port; The backward inference unit is used to input the retrieval conclusion data into the backward inference port and collect the backward inference output port data as verification data. The comparison unit is used to compare the verification data and the retrieval conclusion data to obtain the verification result. A construction unit is used to construct the second search engine model when the verification result is valid.

9. A non-volatile storage medium, characterized in that, The non-volatile storage medium includes a stored program, wherein the program, when executed, controls the device where the non-volatile storage medium is located to perform the method described in any one of claims 1 to 4.

10. An electronic device, characterized in that, It includes a processor and a memory; the memory stores computer-readable instructions, and the processor is configured to execute the computer-readable instructions, wherein the computer-readable instructions, when executed, perform the method according to any one of claims 1 to 4.

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