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Short Term Load Forecasting Model Based on Support Vector Machine.

Authors :
Yeung, Daniel S.
Zhi-Qiang Liu
Xi-Zhao Wang
Hong Yan
Dong-Xiao Niu
Qiang Wang
Jin-Chao Li
Source :
Advances in Machine Learning & Cybernetics; 2006, p880-888, 9p
Publication Year :
2006

Abstract

An artificial neural network was used for sample preprocessing in this paper. Firstly, the data points were classified into three types as follows: the high load type, the medium load type and the low load type. Then, the artificial neural network was adopted to forecast the load type of the predict point. Finally, a support vector machine forecasting model was created on the basis of data points whose load type is the same as the predict point. Comparisons were made between different methods. The results show that the model established in this paper is better than other methods in forecasting accuracy and computing speed. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISBNs :
9783540335849
Database :
Supplemental Index
Journal :
Advances in Machine Learning & Cybernetics
Publication Type :
Book
Accession number :
32901513
Full Text :
https://doi.org/10.1007/11739685_92