A Method for Predicting Chaotic Time Series based on a Local Approximation Technique

Abstract

An improved method based on a local approximation technique is presented for predicting chaotic time series.In the local approximation technique,a state space is reconstructed from a time series using delay coordinates and then a local predictor is constructed on the basis of the motion of the nearest neighbors in the state space. To increase the prediction accuracy of the local approximation,a new method is proposed for selecting the nearest neighbors in the state space.The efficacy of the proposed method is demonstrated using chaotic time series generated by the Ikeda map and the Henon map.