中文摘要：

针对弹体对混凝土材料侵彻深度问题，通过量纲分析和神经网络理论，建立了弹体侵彻深度h网络输出量与弹体长度lp、弹的长径比lp/d、弹体形状系数砂、弹体与混凝土的比强度σyt／σyp弹体与混凝土的密度比ρp／ρt等13个网络输入量之间的非线性映射关系。并采用RBF网络模型，通过Forrestal等文献的试验样本对网络模型训练，获得了弹体对混凝土材料侵彻深度的网络模型，输出结果满意。

英文摘要：

In this article, nonlinear mapping relation between input of 13 variables of lp and σyt/σyp etc. , and output of penetration depth is established by dimensional analysis and theory of artificial neural networks for problem of penetration depth of projectiles into concrete. Moreover, a satisfied output about penetration depth from RBF neural network is gotten by a group of input sets and corresponding output sets, which comes from M. J. Forrestal ＇ s document.