Time Series Forecasting: Obtaining Long Term Trends with Self-Organizing Maps

Author

G. Simon
Amaury Lendasse, Missouri University of Science and TechnologyFollow
M. Cottrell
J. C. Fort
M. Verleysen

Abstract

Kohonen Self-Organisation Maps Are a Well Know Classification Tool, Commonly Used in a Wide Variety of Problems, But with Limited Applications in Time Series Forecasting Context. in This Paper, We Propose a Forecasting Method Specifically Designed for Multi-Dimensional Long-Term Trends Prediction, with a Double Application of the Kohonen Algorithm. Practical Applications of the Method Are Also Presented. © 2005 Elsevier B.v. All Rights Reserved.

Recommended Citation

G. Simon et al., "Time Series Forecasting: Obtaining Long Term Trends with Self-Organizing Maps," Pattern Recognition Letters, vol. 26, no. 12, pp. 1795 - 1808, Elsevier, Sep 2005.

The definitive version is available at https://doi.org/10.1016/j.patrec.2005.03.002

Department(s)

Engineering Management and Systems Engineering

Keywords and Phrases

Long-term trends; Self-organizing maps; Time series forecasting

International Standard Serial Number (ISSN)

0167-8655

Document Type

Article - Conference proceedings

Document Version

Citation

File Type

text

Language(s)

English

Rights

© 2024 Elsevier, All rights reserved.

Publication Date

01 Sep 2005