A Predictive Model of Nonlinear System Based on Generalized Regression Neural Network

Abstract

Generalized regression neural network (GRNN) is usually applied to the function approximation. Based on the principle of GRNN, this paper presents a method for the predictive model of nonlinear complex system. The presented algorithm is applied to the training and predicting process of the nonlinear model. The simulations show the presented method has good effects on predicting the dynamic process of the nonlinear model, and could be applied on the prediction control for nonlinear systems satisfactorily