Research on Intelligent Prediction Method of Wargaming Air Mission

doi:10.16182/j.issn1004731x.joss.21-0717

Abstract

Abstract:

The efficient, accurate and automatic judgment of the combat mission or intention of the enemy's air targets in the battlefield is the basis of situation awareness and the key to the allocation of auxiliary combat resources. Combined with the calculation characteristics of feed forward deep neural network and long-term and short-term memory network model, two targeted basic index learners are designed, and then the weighted combination is carried out according to the cross entropy of the basic index, which can be used to further train the evaluation index of the learner. It can not only effectively prevent the model from over fitting, but also improve the efficiency of model training. The test results show that the proposed model can prevent the over fitting of the model and judge the combat mission or intention of the enemy target with high accuracy.

Key words: air mission, deep learning, situation awareness, wargaming, allocation of resources

CLC Number:

TP391.9

Dayong Zhang, Jingyu Yang, Xi Wu. Research on Intelligent Prediction Method of Wargaming Air Mission[J]. Journal of System Simulation, 2023, 35(1): 212-220.

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time	ID	entity	lng	lat	course	missions
6.053 984 575 835 476	4 906 777	5	49	12	4	5
6.054 841 473 864 61	4 829 856	1	42	40	4	1
6.054 841 473 864 61	4 829 856	1	42	40	16	1
6.054 841 473 864 61	4 831 428	1	42	41	16	1
6.060 554 127 392 174	4 969 783	23	49	5	1	11
6.060 554 127 392 174	4 969 783	23	49	5	2	11

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