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《Proceedings of the Chinese Society of Universities for Electric Power System and its Automation》 2011-04
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Application Profiles of Support Vector Machine in Short-term Load Forecasting

WANG Ben,LENG Bei-xue,ZHANG Xi-hai,SHAN Chong-hao,CONG Zhen(College of Electrical Engineering,South West Jiaotong University, Chengdu 610031,China)  
The application profiles of support vector machine(SVM) in the field of short-term load forecasting(STLF) is summarized in the paper.Based on the principle of SVM and compared with artificial neural network,the superiority of the SVM method in the application of STLF is elaborated.Some problems about the application of SVM,including data pre-processing,the consturcting and current solutions are provided respectively.For a series of SVM-based improvements and some mixed forecasting methods consisting of SVM with other algorithms,a comprehensive summary is given,from the perpective of the mechanism about SVM algorithm being applied to load forecasting,and the elevation of prediction accuracy and speed.Meantime,some key issues needing further discussion are put forward.Finally,some key issues about SVM-based STLF are summarized and some recommendations are given.
【CateGory Index】: TM715
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