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Chaotic time series multi-step direct prediction with partial least squares regression
Author(s): Liu Zunxiong, Liu Jianhui
Pages: 611-
615
Year: 2007
Issue:
3
Journal: JOURNAL OF SYSTEMS ENGINEERING AND ELECTRONICS
Keyword: chaotic series prediction; multi-step; local model; partial least squares.;
Abstract: 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.
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