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Application of SVM based on rough set in smart grid energy-saving prediction

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2 Author(s)
Ting Wang ; Department of Economic Management, North China Electric Power University, Baoding Hebei China ; Lijuan Qin

With the global resources being scarce, it is the common goal of global power industry to build a reasonable energy-saving smart grid system. It combines rough set (RS) with the SVM in this paper, reduces performance of SVM input space and the dimension of input space with the reduction of RS, so as to improve SVM predict accuracy. The experimental results prove this method of RS-SVM is to high predict 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