Time Series Forecasting: Obtaining Long Term Trends with Self-Organizing Maps - Archive ouverte HAL
Article Dans Une Revue Pattern Recognition Letters Année : 2005

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

Résumé

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.

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Dates et versions

hal-00122749 , version 1 (08-01-2007)

Identifiants

Citer

Geoffroy Simon, Amaury Lendasse, Marie Cottrell, Jean-Claude Fort, Michel Verleysen. Time Series Forecasting: Obtaining Long Term Trends with Self-Organizing Maps. Pattern Recognition Letters, 2005, 26 n° 12, pp.1795-1808. ⟨10.1016/j.patrec.2005.03.002⟩. ⟨hal-00122749⟩
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