Multiple architecture system for wind speed prediction

被引:140
作者
Bouzgou, Hassen [1 ]
Benoudjit, Nabil [1 ]
机构
[1] Univ Batna, Dept Elect, Fac Sci Ingenieur, Batna 05000, Algeria
关键词
Wind speed prediction; Multiple architecture system; Neural networks; Support vector machines; Fusion; SHORT-TERM PREDICTION; NEURAL-NETWORKS; COMBINATION; GENERATION; FORECASTS; MODEL;
D O I
10.1016/j.apenergy.2011.01.037
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
080707 [能源环境工程]; 082001 [油气井工程];
摘要
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. (C) 2011 Elsevier Ltd All rights reserved.
引用
收藏
页码:2463 / 2471
页数:9
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