Direct and Recursive Prediction of Time Series using Mutual Information Selection

Author

Yongnan Ji
Jin Hao
Nima Reyhani
Amaury Lendasse, Missouri University of Science and TechnologyFollow

Abstract

This Paper Presents a Comparison between Direct and Recursive Prediction Strategies. in Order to Perform the Input Selection, an Approach based on Mutual Information is Used. the Mutual Information is Computed between All the Possible Input Sets and the Outputs. Least Squares Support Vector Machines Are Used as Non-Linear Models to Avoid Local Minima Problems. Results Are Illustrated on the Poland Electricity Load Benchmark and They Show the Superiority of the Direct Prediction Strategy. © Springer-Verlag Berlin Heidelberg 2005.

Recommended Citation

Y. Ji et al., "Direct and Recursive Prediction of Time Series using Mutual Information Selection," Lecture Notes in Computer Science, vol. 3512, pp. 1010 - 1017, Springer, Jan 2005.

The definitive version is available at https://doi.org/10.1007/11494669_124

Department(s)

Engineering Management and Systems Engineering

Keywords and Phrases

Direct Prediction; Least Squares Support Vector Machines and Prediction Strategy; Mutual Information; Recursive Prediction; Time Series Prediction

International Standard Serial Number (ISSN)

0302-9743

Document Type

Article - Conference proceedings

Document Version

Citation

File Type

text

Language(s)

English

Rights

© 2024 Springer, All rights reserved.

Publication Date

01 Jan 2005