Nonlinear time series modelling and prediction using Gaussian RBF network with evolutionary structure optimisation

Abstract

An evolutionary structure optimisation method for the Gaussian radial basis function network is presented for modelling and predicting nonlinear time series. The generalisation performance is significantly improved with a much smaller network, compared with that of the previous clustering and least square learning method.