Chaotic time series multi-step direct prediction with partial least squares regression

作     者：Liu Zunxiong Liu Jianhui 

作者机构：School of Information Engineering Huadong Jiaotong Univ Nachang 330013 P.R. China 

出 版 物：《Journal of Systems Engineering and Electronics》 (系统工程与电子技术（英文版）)

年 卷 期：2007年第18卷第3期

页      面：611-615页

核心收录：

学科分类：0711[理学-系统科学] 07[理学] 071101[理学-系统理论] 

主　　题：chaotic series prediction multi-step, local model partial least squares. 

摘      要：Considering chaotic time series multi-step prediction, multi-step direct prediction model based on partial least squares （PLS） is proposed in this article, where PLS, the method for predicting a set of dependent variables forming a large set of predictors, is used to model the dynamic evolution between the space points and the corresponding future points. The model can eliminate error accumulation with the common single-step local model algorithm~ and refrain from the high multi-collinearity problem in the reconstructed state space with the increase of embedding dimension. Simulation predictions are done on the Mackey-Glass chaotic time series with the model. The satisfying prediction accuracy is obtained and the model efficiency verified. In the experiments, the number of extracted components in PLS is set with cross-validation procedure.