Research on Damage Effect Classification in Wargame Replay Data Based on Deep Neural Network

In recent years, wargame competitions have become more and more important. However, there is no targeted tools to analyze the massive wargame data, which can be analyzed to increase the probability of winning. In this paper we focus on the analysis of direct aiming attack data in the wargame replay data, which is very important in the wargame confrontation, but there are many factors affecting the damage effect, so the calculation rules are complicated. In this paper we propose a model of deep neural network can obtain a good training effect, which can accurately predict the damage effect in various complex battlefield situations.