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Multiple architecture system for wind speed prediction
Authors:Hassen Bouzgou  Nabil Benoudjit
Affiliation:Département d’Electronique, Université de Batna, Avenue Boukhlouf Med El Hadi, 05000 Batna, Algeria
Abstract:A new approach based on multiple architecture system (MAS) for the prediction of wind speed is proposed. The motivation behind the proposed approach is to combine the complementary predictive powers of multiple models in order to improve the performance of the prediction process. The proposed MAS can be implemented by associating the predictions obtained from the different regression algorithms (MLR, MLP, RBF and SVM) making up the ensemble by three fusion strategies (simple, weighted and non-linear). The efficiency of the proposed approach has been assessed on a real data set recorded from seven locations in Algeria during a period of 10 years. The experimental results point out that the proposed MAS approach is capable of improving the precision of the wind speed prediction compared to the traditional prediction methods.
Keywords:Wind speed prediction   Multiple architecture system   Neural networks   Support vector machines   Fusion
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