Multiple architecture system for wind speed prediction |
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Authors: | Hassen Bouzgou Nabil Benoudjit |
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Affiliation: | Département d’Electronique, Université de Batna, Avenue Boukhlouf Med El Hadi, 05000 Batna, Algeria |
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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. |
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Keywords: | Wind speed prediction Multiple architecture system Neural networks Support vector machines Fusion |
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