Multi-objective structure selection for radial basis function networks based on genetic algorithm

Radial basis function (RBF) network is well known as a good performance approach to nonlinear system modeling. Though structure selection of RBF network is an important issue, the framework of this problem has not been established. In this paper, we propose multiobjective structure selection method for RBF networks based on MOGA (multiobjective genetic algorithm). The structure of RBF networks is encoded to the chromosomes in GA, then evolved toward to Pareto-optimum for multiobjective functions concerned with model accuracy and complexity. Some numerical simulation results indicate the applicability of the proposed approach.