RBF网络在混凝土强度研究中的应用

Study of Strength of Concrete Using RBF Neural Networks

本文以混凝土抗压强度建模为例 ,介绍一种自组织学习的 RBF算法 ,并与广受欢迎的 BP算法比较。仿真结果表明 ,RBF网络的学习速度显著加快 ,并具有较好的泛化能力 ,能有效地应用于混凝土领域。

This paper is concerned with the use of radial basis function (RBF) neural networks aimed at analysis of strength of concrete. A sort of RBF algorithm is introduced to model the strength of concrete. Simulation shows that the pace of learning of this RBF net is substantially faster than that encountered in popular BP network and the generalization ability of this network is also better. So it is effective to use this RBF net in the field of concrete.