• DocumentCode
    582222
  • Title

    Research on intelligent forecasting method of medium and long-term electricity load

  • Author

    Wang Deji ; Lian Jie ; Xie Junming

  • Author_Institution
    Henan Radio & Telev. Univ., Zhengzhou, China
  • fYear
    2012
  • fDate
    25-27 July 2012
  • Firstpage
    3928
  • Lastpage
    3931
  • Abstract
    Because traditional prediction algorithm can not accurately forecast long-term electricity load, chaos SVM prediction algorithm was introduced and some of its characteristics were discussed. The kernel function was chosen under the guidance of the geometric information. The experiment shows that the algorithm is more accurate and effective than the others.
  • Keywords
    chaos; load forecasting; prediction theory; support vector machines; chaos SVM prediction algorithm; geometric information; intelligent forecasting method; kernel function; long-term electricity load forecasting; medium-term electricity load forecasting; prediction algorithm; Chaos; Electricity; Electronic mail; Forecasting; Prediction algorithms; Support vector machines; TV; Chaos; Prediction; SVM;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control Conference (CCC), 2012 31st Chinese
  • Conference_Location
    Hefei
  • ISSN
    1934-1768
  • Print_ISBN
    978-1-4673-2581-3
  • Type

    conf

  • Filename
    6390612