PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Time series prediction using DirRec strategy
Antti Sorjamaa and Amaury Lendasse
In: ESANN 2006, European Symposium on Artificial Neural Networks, 26-28 April 2006, Bruges (Belgium).

Abstract

This paper demonstrates how the selection of Prediction Strategy is important in the Long-Term Prediction of Time Series. Two strategies are already used in the prediction purposes called Recursive and Direct. This paper presents a third one, DirRec, which combines the advantages of the two already used ones. A simple k-NN approximation method is used and all three strategies are applied to two benchmarks: Santa Fe and Poland Electricity Load time series.

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EPrint Type:Conference or Workshop Item (Talk)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Computational, Information-Theoretic Learning with Statistics
Learning/Statistics & Optimisation
Theory & Algorithms
ID Code:2582
Deposited By:Amaury Lendasse
Deposited On:22 November 2006