Application of SVM based on rough set in electricity prices forecasting

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...

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Bibliographic Details
Published in2010 2nd Conference on Environmental Science and Information Application Technology Vol. 2; pp. 317 - 320
Main Authors Ting Wang, Lijuan Qin
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.07.2010
Subjects
Electricity Markets
Electricity Price Forecasting
Rough Set
Support Vector Machine
Support vector machines
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ISBN142447387X
9781424473878
DOI10.1109/ESIAT.2010.5567360

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Summary: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.
ISBN:142447387X
9781424473878
DOI:10.1109/ESIAT.2010.5567360