A wargame situation prediction method based on a graph neural network GraphVAE
In the process of the battle between the enemy and us on the battlefield, accurately predicting the deployment of the enemy forces will be beneficial to our combat. Based on the situation data of wargame, this paper proposes a method for predicting the unknown operator position of the enemy by train...
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| Format: | Article |
| Language: | zho |
| Published: |
Editorial Office of Command Control and Simulation
2023-10-01
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| Series: | Zhihui kongzhi yu fangzhen |
| Subjects: | |
| Online Access: | https://www.zhkzyfz.cn/fileup/1673-3819/PDF/1673-3819(2023)05-0129-08.pdf |
| _version_ | 1797660569412567040 |
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| author | YU Xiaohan, WANG Qidi, YU Kun |
| author_facet | YU Xiaohan, WANG Qidi, YU Kun |
| author_sort | YU Xiaohan, WANG Qidi, YU Kun |
| collection | DOAJ |
| description | In the process of the battle between the enemy and us on the battlefield, accurately predicting the deployment of the enemy forces will be beneficial to our combat. Based on the situation data of wargame, this paper proposes a method for predicting the unknown operator position of the enemy by training Graph Neural Networks. Firstly, after preprocessing the data, the transformation from situation to graph structure data is realized, and the graph structure data set of wargame situation is constructed for training Graph Neural Networks. Secondly, according to the characteristics of wargame situation and its data, GraphVAE model is modified to complete the graph structure data of wargame situation. Finally, a method for calculating the position of the enemy operator based on the completed graph structure data is designed. The effectiveness and feasibility of the proposed method are verified by experiments. |
| first_indexed | 2024-03-11T18:32:46Z |
| format | Article |
| id | doaj.art-4b85ca99be3841a3b8a3280ce085bd45 |
| institution | Directory Open Access Journal |
| issn | 1673-3819 |
| language | zho |
| last_indexed | 2024-03-11T18:32:46Z |
| publishDate | 2023-10-01 |
| publisher | Editorial Office of Command Control and Simulation |
| record_format | Article |
| series | Zhihui kongzhi yu fangzhen |
| spelling | doaj.art-4b85ca99be3841a3b8a3280ce085bd452023-10-13T09:05:10ZzhoEditorial Office of Command Control and SimulationZhihui kongzhi yu fangzhen1673-38192023-10-0145512913610.3969/j.issn.1673-3819.2023.05.018A wargame situation prediction method based on a graph neural network GraphVAEYU Xiaohan, WANG Qidi, YU Kun0College of Command & Control Systems, Army Engineering University of PLA,Nanjing 210007, ChinaIn the process of the battle between the enemy and us on the battlefield, accurately predicting the deployment of the enemy forces will be beneficial to our combat. Based on the situation data of wargame, this paper proposes a method for predicting the unknown operator position of the enemy by training Graph Neural Networks. Firstly, after preprocessing the data, the transformation from situation to graph structure data is realized, and the graph structure data set of wargame situation is constructed for training Graph Neural Networks. Secondly, according to the characteristics of wargame situation and its data, GraphVAE model is modified to complete the graph structure data of wargame situation. Finally, a method for calculating the position of the enemy operator based on the completed graph structure data is designed. The effectiveness and feasibility of the proposed method are verified by experiments.https://www.zhkzyfz.cn/fileup/1673-3819/PDF/1673-3819(2023)05-0129-08.pdfsituation prediction|graph structure data|graph neural network|wargame situation |
| spellingShingle | YU Xiaohan, WANG Qidi, YU Kun A wargame situation prediction method based on a graph neural network GraphVAE Zhihui kongzhi yu fangzhen situation prediction|graph structure data|graph neural network|wargame situation |
| title | A wargame situation prediction method based on a graph neural network GraphVAE |
| title_full | A wargame situation prediction method based on a graph neural network GraphVAE |
| title_fullStr | A wargame situation prediction method based on a graph neural network GraphVAE |
| title_full_unstemmed | A wargame situation prediction method based on a graph neural network GraphVAE |
| title_short | A wargame situation prediction method based on a graph neural network GraphVAE |
| title_sort | wargame situation prediction method based on a graph neural network graphvae |
| topic | situation prediction|graph structure data|graph neural network|wargame situation |
| url | https://www.zhkzyfz.cn/fileup/1673-3819/PDF/1673-3819(2023)05-0129-08.pdf |
| work_keys_str_mv | AT yuxiaohanwangqidiyukun awargamesituationpredictionmethodbasedonagraphneuralnetworkgraphvae AT yuxiaohanwangqidiyukun wargamesituationpredictionmethodbasedonagraphneuralnetworkgraphvae |