Method, system and program product for converting battle examples for wargaming

Abstract

The present application belongs to the field of military simulation technology, and specifically discloses a battle example data conversion method, system and program product for war game deduction, which realizes the automatic conversion from multi-source heterogeneous battle example data to standardized and executable war game deduction plan through data preprocessing and element sequence extraction on the multi-source heterogeneous battle example data, and then script generation using the extracted element sequence, thereby improving the battle example data conversion efficiency and the intelligent level of war game deduction; through the fusion and conflict resolution of multi-source elements, high-precision element extraction can be realized, the accuracy of element extraction is ensured, and the battle game deduction example data conversion demand of complex battlefield scenes can be supported; and through the automatic battle example data conversion processing, manual intervention can be reduced, the efficiency and quality of battle example data conversion are improved, and the present application is suitable for large-scale battle example library.

Description

Technical Field

[0001] This invention belongs to the field of military simulation technology, specifically relating to methods, systems, and program products for converting war case data for war game simulations. Background Technology

[0002] Wargaming simulates war scenarios, assisting commanders in training and operational planning. It is an important method for studying war, supporting decision-making, and training command personnel. Traditional wargaming scenario construction relies heavily on manual writing by professionals, which is inefficient and limited by individual expert experience. Historical war examples contain rich operational patterns and are valuable resources for constructing high-quality wargaming scenarios. However, war example data typically exists in diverse and heterogeneous formats such as text reports and plotted charts, resulting in inconsistent formats and structures, leading to inefficient data processing and making it unsuitable for direct use in intelligent wargaming systems. Therefore, there is an urgent need for an efficient and intelligent war example data transformation method that can automatically extract key operational elements from these complex war example data and directly transform them into an executable wargaming platform. Summary of the Invention

[0003] The purpose of this invention is to provide a method, system, and program product for converting war case data for war game simulations, in order to solve the above-mentioned problems existing in the prior art.

[0004] To achieve the above objectives, the present invention adopts the following technical solution: Firstly, it provides methods for converting case study data for wargaming simulations, including: Obtain a multi-source heterogeneous battle case data set for the same battle case, wherein the multi-source heterogeneous battle case data set contains several battle case data sets; Content identification is performed on each battle case data in the multi-source heterogeneous battle case data set to obtain the multimodal battle case content of each battle case data; The multimodal battle case content of each battle case data is subjected to battle case element extraction to obtain several battle case element groups, and the source identifier of each battle case element group is marked. The battle case element group includes action time, spatial location, action event, action subject, subject scale, equipment configuration, combat rules and action result; Based on the action time, time matching is performed on each battle example element group to obtain the corresponding time matching results. Based on the time matching results, each battle example element group within the same time period is divided into the same battle example element cluster. Multi-source element fusion is performed on the battle example element groups in each battle example element cluster, and during the fusion process, the confidence level of the conflict battle example elements in each battle example element group is screened based on the source identifier to obtain the fused battle example element group. The elements of each integrated battle case are arranged sequentially based on the order of the action time to obtain the battle case element sequence. The war game execution script of the target war game system is generated by using the sequence of battle case elements, and the war game execution script is sent to the target war game system.

[0005] In one possible design, the battle case data includes battle case text data and / or battle case chart data. The step of performing content recognition on each battle case data in the multi-source heterogeneous battle case data set to obtain the multimodal battle case content of each battle case data includes: Optical character recognition is performed on the textual and / or graphical data of each battle case to obtain the multimodal battle case content of each battle case.

[0006] In one possible design, the multimodal battle case content of each battle case data is processed to extract battle case elements, resulting in several battle case element groups, including: A pre-trained feature extraction model is used to extract features from the multimodal battle case data of each battle case, resulting in several battle case feature groups. The feature extraction model adopts the BERT model.

[0007] In one possible design, the step of performing time matching on each battle example element group based on the action time to obtain the corresponding time matching results, and classifying battle example element groups within the same time period into the same battle example element cluster based on the time matching results, includes: Determine the action time of each battle example element group, and determine that battle example element groups with the same action time or an action time difference within a set range are in the same time period; Grouping the elements of each battle case within the same time period into the same battle case element cluster.

[0008] In one possible design, the multi-source element fusion of the battle example element groups in each battle example element cluster is performed, and during the fusion process, the confidence level of the conflict battle example elements in each battle example element group is screened based on the source identifier to obtain the fused battle example element group, including: Compare the various battle example element groups within the same battle example element cluster to determine whether the corresponding battle example elements in each battle example element group are consistent. When it is determined that the corresponding battle elements in each battle element group are consistent, the same battle elements in each battle element group are merged into the corresponding first fused battle element. When it is determined that the corresponding battle example elements in each battle example element group are inconsistent, the inconsistent battle example element items are regarded as conflicting battle example element items between each battle example element group. Based on the source identifier of each battle case element group, the confidence level of the conflict battle case element items between each battle case element group is filtered, and the target battle case element of the filtered conflict battle case element item is used as the corresponding second fused battle case element. The elements of each first integrated battle case and / or each second integrated battle case are combined to obtain the integrated battle case element group of the corresponding battle case element cluster.

[0009] In one possible design, the confidence screening of conflict battle example elements among each battle example element group based on the source identifier of each battle example element group includes: The type of battle case data to which each battle case element group belongs is determined based on the source identifier of each battle case element group, and the authority index W of each battle case element group is determined based on the type of battle case data to which it belongs, where 0≤W≤1; Each battle example element group is input into the large language model to evaluate the element clarity, and the clarity index Q of each battle example element group is obtained, 0≤Q≤1; Determine the consistency index R of each battle example element group with respect to the corresponding conflict battle example element item, R = (X+1) / Y, where X represents the number of other battle example element groups that are consistent with the corresponding battle example element group in the corresponding conflict battle example element item, and Y represents the number of all battle example element groups in the corresponding battle example element cluster. The confidence level of each battle example element group for the corresponding conflict battle example element item is calculated using the authority index W, clarity index Q, and consistency index R for each battle example element group. The battle example element group with the highest confidence level for the corresponding conflict battle example element item is taken as the target battle example element group, and the battle example elements of the target battle example element group in the corresponding conflict battle example element item are taken as the target battle example elements of the corresponding conflict battle example element item.

[0010] In one possible design, the calculation of the confidence level of each battle example element group for the corresponding conflict battle example element item using the authority index W, clarity index Q, and consistency index R for each battle example element group includes: The authority index W, clarity index Q, and consistency index R for the corresponding conflict battle element items of each battle example element group are substituted into the preset confidence formula for calculation to obtain the confidence of each battle example element group for the corresponding conflict battle element item. The confidence formula is F=W×(α×Q+β×R), where F is the confidence, and α and β are the set first weight coefficient and second weight coefficient, respectively.

[0011] Secondly, a war case data conversion system for wargaming simulations is provided, including a data acquisition unit, a content recognition unit, an element extraction unit, a time matching unit, an element fusion unit, a sequence construction unit, and a script generation unit, wherein: The data acquisition unit is used to acquire a multi-source heterogeneous battle case data set for the same battle case, wherein the multi-source heterogeneous battle case data set contains several battle case data. The content recognition unit is used to perform content recognition on each battle case data in the multi-source heterogeneous battle case data set to obtain the multimodal battle case content of each battle case data. The element extraction unit is used to extract elements from the multimodal battle case content of each battle case data, obtain several battle case element groups, and mark the source identifier of each battle case element group. The battle case element group includes action time, spatial location, action event, action subject, subject scale, equipment configuration, combat rules and action result. The time matching unit is used to perform time matching on each battle example element group according to the action time, obtain the corresponding time matching results, and classify the battle example element groups within the same time period into the same battle example element cluster according to the time matching results. The element fusion unit is used to perform multi-source element fusion on the battle example element groups in each battle example element cluster, and to perform confidence screening on the conflict battle example elements of each battle example element group based on the source identifier during the fusion process to obtain the fused battle example element group. The sequence construction unit is used to sequentially arrange the elements of each integrated battle case based on the order of action time to obtain the battle case element sequence; The script generation unit is used to generate the war game execution script of the target war game simulation system using the sequence of battle example elements, and to send the war game execution script to the target war game simulation system.

[0012] Thirdly, it provides a system for converting war game data into war game simulations, including: Memory, used to store instructions; The processor is configured to read instructions stored in the memory and execute any one of the methods for converting war game data for war game simulation as described in the first aspect above, according to the instructions.

[0013] Fourthly, a computer-readable storage medium is provided, on which instructions are stored, which, when executed on a computer, cause the computer to perform any one of the war game data conversion methods described in the first aspect. Simultaneously, a computer program product is also provided, which, when executed on a computer, performs any one of the war game data conversion methods described in the first aspect.

[0014] Beneficial effects: This invention preprocesses and extracts element sequences from multi-source heterogeneous war case data, and then uses the extracted element sequences to generate scripts. This enables the automated transformation from multi-source heterogeneous war case data to standardized, executable war game scenarios, improving the efficiency of war case data transformation and the intelligence level of war game simulations. Through the fusion and conflict resolution of multi-source elements, high-precision element extraction can be achieved, ensuring the accuracy of element extraction and supporting the transformation needs of war game simulation war case data in complex battlefield scenarios. Furthermore, through automated war case data transformation processing, manual intervention can be reduced, improving the efficiency and quality of war case data transformation, making it suitable for large-scale war case databases. Attached Figure Description

[0015] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0016] Figure 1 This is a flowchart illustrating the method in Embodiment 1 of the present invention; Figure 2 This is a schematic diagram of the system configuration in Embodiment 2 of the present invention; Figure 3 This is a schematic diagram of the system configuration in Embodiment 3 of the present invention. Detailed Implementation

[0017] It should be noted that the descriptions of these embodiments are intended to aid in understanding the invention and do not constitute a limitation thereof. The specific structural and functional details disclosed herein are merely for describing exemplary embodiments of the invention. However, the invention may be embodied in many alternative forms and should not be construed as being limited to the embodiments described herein.

[0018] It should be understood that, unless otherwise explicitly specified and limited, the corresponding terms should be interpreted broadly. For example, "connection" can be a fixed connection, a detachable connection, or an integral connection; it can be a direct connection or an indirect connection through an intermediate medium; it can be a connection within two components. Those skilled in the art can understand the specific meaning of the above terms in the embodiments according to the specific circumstances.

[0019] Specific details are provided in the following description to provide a complete understanding of the exemplary embodiments. However, those skilled in the art will understand that the exemplary embodiments can be implemented without these specific details. For example, apparatus may be shown in block diagrams to avoid obscuring the examples with unnecessary details. In other embodiments, well-known processes, structures, and techniques may be omitted with non-essential details to avoid obscuring the embodiments.

[0020] Example 1: This embodiment provides a method for converting war game data for war game simulations, which can be applied to corresponding data processing terminals, such as... Figure 1 As shown, the method includes the following steps: S1. Obtain a multi-source heterogeneous battle case data set for the same battle case, wherein the multi-source heterogeneous battle case data set contains several battle case data.

[0021] In specific implementation, the terminal first acquires a multi-source heterogeneous battle case data set for the same battle case. The multi-source heterogeneous battle case data set contains several battle case data, which includes battle case text data (such as battle history text, combat report, record description text, etc.) and / or battle case chart data (such as equipment parameter table, command organization list, plotted map, etc.).

[0022] S2. Perform content identification on each battle case data in the multi-source heterogeneous battle case data set to obtain the multimodal battle case content of each battle case data.

[0023] In practice, the terminal can perform optical character recognition (OCR) on the textual and / or graphical data of each battle case, and then analyze and normalize the recognition results to obtain the multimodal battle case content of each battle case.

[0024] S3. Extract case elements from the multimodal case content of each case data to obtain several case element groups, and mark the source identifier of each case element group. The case element group includes action time, spatial location, action event, action subject, subject scale, equipment configuration, combat rules and action result.

[0025] In practical implementation, the terminal can utilize a pre-trained element extraction model to extract elements from the multimodal content of each battle case study, resulting in several battle case element groups. For example, the element extraction model can be a BERT model trained and optimized using a military corpus. These battle case element groups include, but are not limited to, action time, spatial location, action event, action subject, subject scale, equipment configuration, combat rules, and action result. When extracting each battle case element group, the terminal also needs to label the source identifier of each battle case element group to indicate which battle case data it originates from, so that it can be used for subsequent battle case element conflict fusion.

[0026] S4. Perform time matching on each battle example element group according to the action time to obtain the corresponding time matching results, and classify the battle example element groups within the same time period into the same battle example element cluster according to the time matching results.

[0027] In practice, the terminal first determines the action time of each case element group, and determines that case element groups with the same action time or an action time difference within a set range are in the same time period. Then, case element groups in the same time period are divided into the same case element cluster.

[0028] S5. Perform multi-source element fusion on the battle example element groups in each battle example element cluster, and filter the confidence of the conflict battle example elements in each battle example element group based on the source identifier during the fusion process to obtain the fused battle example element group.

[0029] In practice, the terminal can compare the various battle example element groups within the same battle example element cluster to determine whether the corresponding battle example elements in each battle example element group are consistent. When it is determined that the corresponding battle example elements in each battle example element group are consistent, the identical battle example elements in each battle example element group are merged (selected) into the corresponding first fused battle example element, that is, the battle example elements of the identical battle example element items in each battle example element group are selected as the first fused battle example element of the corresponding item.

[0030] When it is determined that the corresponding battle example elements in each battle example element group are inconsistent, the inconsistent battle example element items are regarded as conflict battle example element items between each battle example element group. Then, based on the source identifier of each battle example element group, the confidence level of the conflict battle example element items between each battle example element group is filtered, and the target battle example element of the filtered conflict battle example element item is regarded as the corresponding second fused battle example element.

[0031] For example, the terminal can determine the type of battle case data (such as official battle reports, authoritative military works, journal case analysis, etc.) of each battle case element group based on its source identifier, and determine the authority index W of each battle case element group based on its type of battle case data (e.g., by substituting the type of battle case data into a pre-configured authority index classification table for matching, to determine the authority index corresponding to the type of battle case data in the authority index classification table), 0≤W≤1. Each battle case element group can be input into a large language model (a Transformer architecture large language model trained on a corpus) for element clarity evaluation to obtain the clarity index Q of each battle case element group, 0≤Q≤1. The consistency index R of each battle example element group with respect to the corresponding conflict battle example element item can be determined, R = (X+1) / Y, where X represents the number of other battle example element groups that are consistent with the corresponding battle example element group in the corresponding conflict battle example element item, and Y represents the number of all battle example element groups in the corresponding battle example element cluster. For example, if the battle example element of battle example element group a in the corresponding conflict battle example element item is b, and there are 2 other battle example element groups in the same battle example element cluster that are the same as b in the corresponding conflict battle example element item, and there are a total of 10 battle example element groups in the same battle example element cluster, then the consistency index R of battle example element group a with respect to the corresponding conflict battle example element item is R = (2+1) / 10 = 0.3, and so on.

[0032] Then, the confidence level of each battle example element group for the corresponding conflict battle example element item is calculated using the authority index W, clarity index Q, and consistency index R of each battle example element group. For example, the confidence level of each battle example element group for the corresponding conflict battle example element item is calculated by substituting the authority index W, clarity index Q, and consistency index R of each battle example element group into the preset confidence level formula. The confidence level formula is F=W×(α×Q+β×R), where F is the confidence level, and α and β are the set first weight coefficient and second weight coefficient, respectively.

[0033] Then, the battle example element group with the highest confidence level for the corresponding conflict battle example element item is taken as the target battle example element group, and the battle example elements of the target battle example element group in the corresponding conflict battle example element item are taken as the target battle example elements of the corresponding conflict battle example element item, that is, the second fused battle example elements of the corresponding conflict battle example element item.

[0034] Finally, the terminal combines each of the first fusion battle case elements and / or each of the second fusion battle case elements to obtain the fusion battle case element group of the corresponding battle case element cluster.

[0035] S6. Arrange the elements of each integrated battle case in sequence based on the order of action time to obtain the battle case element sequence.

[0036] In practice, the terminal can sequentially arrange the various integrated battle case element groups according to the order of their action times to obtain a battle case element sequence.

[0037] S7. Generate the wargaming execution script for the target wargaming system using the sequence of battle example elements, and send the wargaming execution script to the target wargaming system.

[0038] In practice, the terminal can generate a war game simulation execution script for the target war game simulation system based on the sequence of war game elements, and then send the war game simulation execution script to the target war game simulation system so that the target war game simulation system can run the war game simulation execution script to perform war game simulation display.

[0039] This method preprocesses and extracts element sequences from multi-source heterogeneous war case data, and then uses the extracted element sequences to generate scripts. This enables the automated transformation from multi-source heterogeneous war case data to standardized, executable war game scenarios, improving the efficiency of war case data transformation and the intelligence level of war game simulations. Through the fusion and conflict resolution of multi-source elements, high-precision element extraction can be achieved, ensuring the accuracy of element extraction and supporting the transformation needs of war game simulation war case data in complex battlefield scenarios. Furthermore, through automated war case data transformation processing, manual intervention can be reduced, improving the efficiency and quality of war case data transformation, making it suitable for large-scale war case databases.

[0040] Example 2: This embodiment provides a system for converting war case data for wargaming simulations, such as... Figure 2 As shown, it includes a data acquisition unit, a content recognition unit, a feature extraction unit, a time matching unit, a feature fusion unit, a sequence construction unit, and a script generation unit, wherein: The data acquisition unit is used to acquire a multi-source heterogeneous battle case data set for the same battle case, wherein the multi-source heterogeneous battle case data set contains several battle case data. The content recognition unit is used to perform content recognition on each battle case data in the multi-source heterogeneous battle case data set to obtain the multimodal battle case content of each battle case data. The element extraction unit is used to extract elements from the multimodal battle case content of each battle case data, obtain several battle case element groups, and mark the source identifier of each battle case element group. The battle case element group includes action time, spatial location, action event, action subject, subject scale, equipment configuration, combat rules and action result. The time matching unit is used to perform time matching on each battle example element group according to the action time, obtain the corresponding time matching results, and classify the battle example element groups within the same time period into the same battle example element cluster according to the time matching results. The element fusion unit is used to perform multi-source element fusion on the battle example element groups in each battle example element cluster, and to perform confidence screening on the conflict battle example elements of each battle example element group based on the source identifier during the fusion process to obtain the fused battle example element group. The sequence construction unit is used to sequentially arrange the elements of each integrated battle case based on the order of action time to obtain the battle case element sequence; The script generation unit is used to generate the war game execution script of the target war game simulation system using the sequence of battle example elements, and to send the war game execution script to the target war game simulation system.

[0041] Example 3: This embodiment provides a system for converting war case data for wargaming simulations, such as... Figure 3 As shown, at the hardware level, it includes: The data interface is used to establish data communication between the processor and external data terminals; Memory, used to store instructions; The processor is used to read instructions stored in the memory and execute the case data conversion method in Embodiment 1 according to the instructions.

[0042] Optionally, the system also includes an internal bus, through which the processor, memory, and data interface can be interconnected. This internal bus can be a PCIe (Peripheral Component Interconnect Eexpress) bus, which can be divided into an address bus, a data bus, a control bus, etc. The memory can include, but is not limited to, Random Access Memory (RAM), Read Only Memory (ROM), Flash Memory, First Input First Output (FIFO), and / or First In Last Out (FILO). The processor can be a general-purpose processor, including a Central Processing Unit (CPU), a Network Processor (NP), etc.; it can also be a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field-Programmable Gate Array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components.

[0043] Example 4: This embodiment provides a computer-readable storage medium storing instructions. When these instructions are executed on a computer, the computer performs the case study data conversion method described in Embodiment 1. The computer-readable storage medium refers to a data storage medium, which may include, but is not limited to, floppy disks, optical disks, hard disks, flash memory, USB flash drives, and / or Memory Sticks. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices.

[0044] This embodiment also provides a computer program product that, when run on a computer, executes the case study data conversion method in Embodiment 1. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device.

[0045] Finally, it should be noted that the above description is merely a preferred embodiment of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for converting case study data for wargaming simulations, characterized in that, include: Obtain a multi-source heterogeneous battle case data set for the same battle case, wherein the multi-source heterogeneous battle case data set contains several battle case data sets; Content identification is performed on each battle case data in the multi-source heterogeneous battle case data set to obtain the multimodal battle case content of each battle case data; The multimodal battle case content of each battle case data is subjected to battle case element extraction to obtain several battle case element groups, and the source identifier of each battle case element group is marked. The battle case element group includes action time, spatial location, action event, action subject, subject scale, equipment configuration, combat rules and action result; Based on the action time, time matching is performed on each battle example element group to obtain the corresponding time matching results. Based on the time matching results, each battle example element group within the same time period is divided into the same battle example element cluster. Multi-source element fusion is performed on the battle example element groups in each battle example element cluster, and during the fusion process, the confidence level of the conflict battle example elements in each battle example element group is screened based on the source identifier to obtain the fused battle example element group. The elements of each integrated battle case are arranged sequentially based on the order of the action time to obtain the battle case element sequence. The war game execution script of the target war game system is generated by using the sequence of battle case elements, and the war game execution script is sent to the target war game system.

2. The method for converting war case data for wargaming according to claim 1, characterized in that, The battle case data includes battle case text data and / or battle case chart data. The step of performing content recognition on each battle case data in the multi-source heterogeneous battle case data set to obtain the multimodal battle case content of each battle case data includes: Optical character recognition is performed on the textual and / or graphical data of each battle case to obtain the multimodal battle case content of each battle case.

3. The method for converting war case data for wargaming according to claim 1, characterized in that, The process of extracting battle element data from the multimodal battle case content of each battle case yields several battle element groups, including: A pre-trained feature extraction model is used to extract features from the multimodal battle case data of each battle case, resulting in several battle case feature groups. The feature extraction model adopts the BERT model.

4. The method for converting war case data for wargaming according to claim 1, characterized in that, The process of matching the elements of each battle example based on the action time to obtain the corresponding time matching results, and then grouping the elements of each battle example within the same time period into the same battle example element cluster based on the time matching results, includes: Determine the action time of each battle example element group, and determine that battle example element groups with the same action time or an action time difference within a set range are in the same time period; Grouping the elements of each battle case within the same time period into the same battle case element cluster.

5. The method for converting war case data for wargaming according to claim 1, characterized in that, The process involves multi-source element fusion of battle example element groups within each battle example element cluster, and during the fusion process, confidence-based screening of conflict battle example elements in each battle example element group is performed based on source identifiers to obtain fused battle example element groups, including: Compare the various battle example element groups within the same battle example element cluster to determine whether the corresponding battle example elements in each battle example element group are consistent. When it is determined that the corresponding battle elements in each battle element group are consistent, the same battle elements in each battle element group are merged into the corresponding first fused battle element. When it is determined that the corresponding battle example elements in each battle example element group are inconsistent, the inconsistent battle example element items are regarded as conflicting battle example element items between each battle example element group. Based on the source identifier of each battle case element group, the confidence level of the conflict battle case element items between each battle case element group is filtered, and the target battle case element of the filtered conflict battle case element item is used as the corresponding second fused battle case element. The elements of each first integrated battle case and / or each second integrated battle case are combined to obtain the integrated battle case element group of the corresponding battle case element cluster.

6. The method for converting war case data for wargaming according to claim 5, characterized in that, The confidence screening of conflict case elements among different case element groups based on their source identifiers includes: The type of battle case data to which each battle case element group belongs is determined based on the source identifier of each battle case element group, and the authority index W of each battle case element group is determined based on the type of battle case data to which it belongs, where 0≤W≤1; Each battle example element group is input into the large language model to evaluate the element clarity, and the clarity index Q of each battle example element group is obtained, 0≤Q≤1; Determine the consistency index R of each battle example element group with respect to the corresponding conflict battle example element item, R = (X+1) / Y, where X represents the number of other battle example element groups that are consistent with the corresponding battle example element group in the corresponding conflict battle example element item, and Y represents the number of all battle example element groups in the corresponding battle example element cluster. The confidence level of each battle example element group for the corresponding conflict battle example element item is calculated using the authority index W, clarity index Q, and consistency index R for each battle example element group. The battle example element group with the highest confidence level for the corresponding conflict battle example element item is taken as the target battle example element group, and the battle example elements of the target battle example element group in the corresponding conflict battle example element item are taken as the target battle example elements of the corresponding conflict battle example element item.

7. The method for converting war case data for wargaming according to claim 6, characterized in that, The calculation of the confidence level of each battle example element group for the corresponding conflict battle example element item using the authority index W, clarity index Q, and consistency index R for each battle example element group includes: The authority index W, clarity index Q, and consistency index R for the corresponding conflict battle element items of each battle example element group are substituted into the preset confidence formula for calculation to obtain the confidence of each battle example element group for the corresponding conflict battle element item. The confidence formula is F=W×(α×Q+β×R), where F is the confidence, and α and β are the set first weight coefficient and second weight coefficient, respectively.

8. A system for converting war case data for wargaming simulations, characterized in that, It includes a data acquisition unit, a content recognition unit, a feature extraction unit, a time matching unit, a feature fusion unit, a sequence construction unit, and a script generation unit, among which: The data acquisition unit is used to acquire a multi-source heterogeneous battle case data set for the same battle case, wherein the multi-source heterogeneous battle case data set contains several battle case data. The content recognition unit is used to perform content recognition on each battle case data in the multi-source heterogeneous battle case data set to obtain the multimodal battle case content of each battle case data. The element extraction unit is used to extract elements from the multimodal battle case content of each battle case data, obtain several battle case element groups, and mark the source identifier of each battle case element group. The battle case element group includes action time, spatial location, action event, action subject, subject scale, equipment configuration, combat rules and action result. The time matching unit is used to perform time matching on each battle example element group according to the action time, obtain the corresponding time matching results, and classify the battle example element groups within the same time period into the same battle example element cluster according to the time matching results. The element fusion unit is used to perform multi-source element fusion on the battle example element groups in each battle example element cluster, and to perform confidence screening on the conflict battle example elements of each battle example element group based on the source identifier during the fusion process to obtain the fused battle example element group. The sequence construction unit is used to sequentially arrange the elements of each integrated battle case based on the order of action time to obtain the battle case element sequence; The script generation unit is used to generate the war game execution script of the target war game simulation system using the sequence of battle example elements, and to send the war game execution script to the target war game simulation system.

9. A system for converting war case data for wargaming simulations, characterized in that, include: Memory, used to store instructions; A processor is configured to read instructions stored in the memory and execute the war case data conversion method for war game simulation as described in any one of claims 1-7 according to the instructions.

10. A computer program product, characterized in that, When the computer program product is run on a computer, it executes the method for converting war game data for war game simulation as described in any one of claims 1-7.

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