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Application of SVM based on rough set in electricity prices forecasting

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2 Author(s)
Ting Wang ; Dept. of Economic Manage., North China Electr. Power Univ., Baoding, China ; Lijuan Qin

Price is a core element of the electricity market, Price forecasting is an important issue of great concern to all participants, in order to improve the accuracy of price forecasting, it introduces rough set and support vector machines for prediction models in the paper, integrates the advantages of each model. The experimental results prove this method of RS-SVM is to improve the prediction accuracy and of great prospect compare to the BP method.

Published in:

Environmental Science and Information Application Technology (ESIAT), 2010 International Conference on  (Volume:2 )

Date of Conference:

17-18 July 2010