Title :
The grey error correction forecast method based on SVR
Author :
Wang, Pei-Guang ; Li, Yang ; Zong, Xiao-ping ; Zhao, Fu-fen ; Yan, Chun-xiao
Author_Institution :
Coll. of Electron. & Inf. Eng., Hebei Univ., Baoding, China
Abstract :
The advantages and disadvantages of grey forecast method are analyzed respectively. The grey error forecast method based on support vector regression (SVR) is proposed in this article. The new method remedy the disadvantages of grey forecast model and weakens the stochastic undulation, avoids the theoretical defects existing in the grey forecast model. The forecast effect is improved for non-linear specimen.
Keywords :
grey systems; load forecasting; power engineering computing; regression analysis; support vector machines; grey error correction forecast method; stochastic undulation; support vector regression; Cybernetics; Educational institutions; Equations; Error correction; Load forecasting; Machine learning; Machine learning algorithms; Power engineering and energy; Predictive models; Support vector machines; Error correction; Grey forecast; Load forecast; SVM; SVR;
Conference_Titel :
Machine Learning and Cybernetics, 2009 International Conference on
Print_ISBN :
978-1-4244-3702-3
Electronic_ISBN :
978-1-4244-3703-0
DOI :
10.1109/ICMLC.2009.5212268
