Time Series Forecasting: Obtaining Long Term Trends with Self-Organizing Maps
Machine Learning
2011-11-09 v1 Statistics Theory
Statistics Theory
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.
Keywords
Cite
@article{arxiv.cs/0701052,
title = {Time Series Forecasting: Obtaining Long Term Trends with Self-Organizing Maps},
author = {Geoffroy Simon and Amaury Lendasse and Marie Cottrell and Jean-Claude Fort and Michel Verleysen},
journal= {arXiv preprint arXiv:cs/0701052},
year = {2011}
}
Comments
\`{a} la suite de la conf\'{e}rence ANNPR, Florence 2003