A WAVELET SUPPORT VECTOR MACHINE COUPLED METHOD FOR TIME SERIES PREDICTION

作者：Ben Mabrouk Anouar^*; Kortas Hedi; Dhifaoui Zouhaier

来源：International Journal of Wavelets, Multiresolution and Information Processing, 2008, 6(6): 851-868.

DOI：10.1142/S0219691308002719

• Maximal Overlap Discrete Wavelet Transform
• Least Squares Support Vector Machine

In this paper, a hybrid scheme for time series prediction is developed based on wavelet decomposition combined with Bayesian Least Squares Support Vector Machine regression. As a filtering step, using the Maximal Overlap Discrete Wavelet Transform, the original time series is mapped on a scale-by-scale basis yielding an outcome set of new time series with simpler temporal dynamic structures. Next, a scale-by-scale Bayesian Least Squares Support Vector Machine predictor is provided. Individual scale predictions are subsequently recombined to yield an overall forecast. The relevance of the suggested procedure is shown on the NINO3 SST anomaly index via a comparison with the existing methods for modeling and prediction.

• 出版日期2008-11