The Design of Beta Basis Function Neural Network Using Hierarchical Genetic Algorithm

We propose an evolutionary method for the design of Beta basis function neural networks (BBFNN). Classical training algorithms start with a predetermined network structure for neural networks. Generally speaking the neural network is either insufficient or over-complicated. This paper describes a hierarchical genetic learning model of the BBFNN. In order to examine the performance of the proposed algorithm, it is used for functional approximation problem. The results obtained have been encouraging.