基于RBF网络的坦克火控系统效能评价仿真

Evaluation of Tank Firepower and Control System’s Effectiveness Based on the RBF Network

利用层次分析法提出了坦克火控系统效能评价指标体系,简要介绍了指标选取的理由。然后,采用提取原始值法和Delphi法取得了几组训练样本,并对所构造的三层RBF神经网络进行仿真训练,当训练精度达到要求后,再运用RBF神经网络对某型坦克火控系统效能进行了仿真评估。结果表明,在选定指标的基础上,用训练好的RBF神经网络评估坦克火控系统效能是合理的,减少了评估中的人为因素,使评估的结果更为可信。研究结果可为在现有武器装备的基础上开发和研制新型坦克火控系统提供理论参考。

In this paper, the index of tank firepower and control system is set up through AHP method and the choice reasons of the index system is analyzed. This article adopts original data and implies the Delphi method to get some training samples. The RBF neural network is trained with the samples. When its training precision achieves the requirement, it is used to simulate and evaluate the main tank＇s firepower and control system. It proves that it＇s reasonable to evaluate the tank＇ firepower and control system with the trained RBF network using the chosen indexes, and it reduces the artificial factors and makes the outcomes more relied. The research outcome can provide the reference for developing new armored equipment.