基于ANN技术的射击效率评定

将BP、RB、GRNN等人工神经网络引入火炮射击效率评定,其运算先确定相关参数、再根据毁伤概率产生输出数据、最后对数据进行检验,对训练好的网络进行仿真,并将计算与网络仿真的结果进行对比.结果表明,训练好的神经网络可较精确逼近解析解的结果,在计算量大的情况下该方法较解析计算更具优势.

The Research on Evaluation of the Fire Efficiency based on Artificial Neural Network Technology

This article introduces the artificial neural network technologies such as BP、RB、GRNN etc into the evaluation of gun fire efficiency,its computation method is:determine first the related parameters;subsequently generate the output data according to damage probability;lastly,verify the data,simulate trained network,and compare the computation to the results of network simulation.The results indicate that the trained neural network can approach precisely to the results of analytic solution.