• DocumentCode
    3597261
  • 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
  • Volume
    3
  • fYear
    2009
  • Firstpage
    1261
  • Lastpage
    1265
  • 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;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Learning and Cybernetics, 2009 International Conference on
  • Print_ISBN
    978-1-4244-3702-3
  • Electronic_ISBN
    978-1-4244-3703-0
  • Type

    conf

  • DOI
    10.1109/ICMLC.2009.5212268
  • Filename
    5212268