A Prediction Method for Nonlinear Correlative Time Series

Abstract

A nonlinear correlative time series prediction method is presented in this paper.It is based on the mutual information of time series and orthogonal polynomial basis neural network. Inputs of network are selected by mutual information, and orthogonal polynomial basis is used as active function.The network is trained by an error iterative learning algorithm.This proposed method for nonlinear time series is tested using two well known time series prediction problems:Gas furnace data time series and Mackey-Glass time series.