
Penetration Depth of Projectiles Into Concrete Using Artificial Neural Network
Li Jianguang1、Li Yongchi1、Wang Yulan2
Strategic Study of CAE ›› 2007, Vol. 9 ›› Issue (8) : 77-81.
Penetration Depth of Projectiles Into Concrete Using Artificial Neural Network
Li Jianguang1、Li Yongchi1、Wang Yulan2
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.
neural networks / dimensional analysis / penetration depth of projectiles into concrete / nonlinear mapping relation / RBF neural networks
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