关键词: 蓝军模型参数, 灰色系统建模, 仿真模型, 深度网络, 拦截弹建模

Abstract:

The modeling of blue army equipment is an indispensable part of adversarial simulation environment construction. Aiming at the limited available parameters of "information-poor" and "small sample" characteristics to the blue system, a deep network-based method is proposed to generate the parameters of blue army equipment model. By injecting the information into the simulation model of the blue army equipment, the simulation data is generated and trained in the deep neural network. The obtained network has a certain generalization ability to the unknown parameters prediction of the same type of equipment and can be used directly in prediction or be the source model for migration learning. The application is verified by the modeling simulation of a certain type of interceptor of blue army in which two kinds of networks, multilayer perceptron and recurrent neural network, are used to learn and predict the proportional guidance coefficients, and the results are good.

Key words: blue army model parameters, grey system modeling, simulation model, deep network, interceptor modeling