Time Series Forecasting: Obtaining Long Term Trends with Self-Organizing Maps
<|reference_start|>Time Series Forecasting: Obtaining Long Term Trends with Self-Organizing Maps: 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.<|reference_end|>
@article{simon2007time,
    title={Time Series Forecasting: Obtaining Long Term Trends with Self-Organizing
  Maps},
    author={Geoffroy Simon (DICE-MLG), Amaury Lendasse (DICE-MLG), Marie Cottrell
  (SAMOS, Matisse), Jean-Claude Fort (SAMOS, Matisse), Michel Verleysen (SAMOS,
  Matisse, Dice-MLG)},
    journal={Pattern Recognition Letter 26 n0; 12 (05/2005) 1795-1808},
    year={2007},
    archivePrefix={arXiv},
    eprint={cs/0701052},
    primaryClass={cs.LG math.ST stat.TH}
}