DocumentCode :
1988650
Title :
Application of SVM based on rough set in smart grid energy-saving prediction
Author :
Wang, Ting ; Qin, Lijuan
Author_Institution :
Dept. of Economic Manage., North China Electr. Power Univ., Baoding, China
Volume :
2
fYear :
2010
fDate :
17-18 July 2010
Firstpage :
313
Lastpage :
316
Abstract :
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.
Keywords :
energy conservation; power engineering computing; rough set theory; smart power grids; support vector machines; BP method; RS-SVM; global power industry; rough set; smart grid energy-saving prediction; Analytical models; Support vector machines; Eenerg-Saving effectiveness; Prediction; Rough Set; Smart Grid; Support Vector Machine;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Environmental Science and Information Application Technology (ESIAT), 2010 International Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-7387-8
Type :
conf
DOI :
10.1109/ESIAT.2010.5567355
Filename :
5567355
Link To Document :
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