基于RBF神经网络的作战效能评估方法

作战效能评估是现代作战模拟中的一个非常重要的环节,受到人们特别的关注.介绍了一种基于改进型RBF神经网络的作战效能评估方法,主要是依据样本数据动态调节网络结构与参数.然后基于EINSTein系统进行实例评估,仿真结果表明改进的RBF神经网络算法具有良好的自学习能力,以及预测精度高、可行性好等优点,可以广泛应用于作战效能的评估工作中.

Evaluation Method of Combat Effectiveness Based on RBF Neural Network

In the modern combat simulation,the evaluation of combat effectiveness is an important link,and suffers the special high attention.An evaluation method of combat effectiveness was proposed based on improved RBF neural network,the method regulated the scale and parameter of network dynamically by the samples.Then an experiment was conducted using EINSTein system.The simulation results show that the improved RBF neural network has the advantages of stronger self-learning ability,high precision and great feasibility.Therefore,the method can be used widely in the evaluation of combat effectiveness.