title: Double quantization of the regressor space for long-term time series prediction: method and proof of stability.
abstract: The Kohonen self-organization map is usually considered as a classification or clustering tool, with only a few applications in time series prediction. In this paper, a particular time series forecasting method based on Kohonen maps is described. This method has been specifically designed for the prediction of long-term trends. The proof of the stability of the method for long-term forecasting is given, as well as illustrations of the utilization of the method both in the scalar and vectorial cases.
authors.affiliation: Machine Learning Group (DICE), Université Catholique de Louvain, Place du Levant 3, B-1348 Louvain-la-Neuve, Belgium. simon@dice.ucl.ac.be
authors.forename: Geoffroy
authors.initials: G
authors.lastname: Simon
authors.forename: Amaury
authors.initials: A
authors.lastname: Lendasse
authors.forename: Marie
authors.initials: M
authors.lastname: Cottrell
authors.forename: Jean-Claude
authors.initials: JC
authors.lastname: Fort
authors.forename: Michel
authors.initials: M
authors.lastname: Verleysen
mesh_terms: D005544:Forecasting; D009010:Monte Carlo Method; D016571:Neural Networks, Computer; D011044:Poland; D011210:Power Plants