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).
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.