• DocumentCode
    2149035
  • Title

    RBF Model Applied to Forecast the Water and Sediment Fluxes in Lijin Section

  • Author

    Yan, Jun ; Cao, Hui ; Wang, Jun ; Liu, Yanfang ; Zhao, Haibin

  • Author_Institution
    North China Univ. of Water Conservancy & Electr. Power, Zhengzhou, China
  • fYear
    2009
  • fDate
    17-19 Oct. 2009
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    The structure of the RBF neural network is introduced. Then the RBF model is build up to forecast the runoff and the sediment transport volume of Lijin section during the flood period and the non-flood period in 11th year according to the former 10 years´ field data. Compared the RBF emulating results with the field data, the forecasting error is analyzed and the methods to improve the forecast precision are put forward.
  • Keywords
    forecasting theory; radial basis function networks; RBF model; forecast precision; forecasting error; sediment flux; water flux; Artificial neural networks; Biological neural networks; Floods; Mouth; Predictive models; Rivers; Sediments; Statistical analysis; Water conservation; Water resources;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image and Signal Processing, 2009. CISP '09. 2nd International Congress on
  • Conference_Location
    Tianjin
  • Print_ISBN
    978-1-4244-4129-7
  • Electronic_ISBN
    978-1-4244-4131-0
  • Type

    conf

  • DOI
    10.1109/CISP.2009.5303860
  • Filename
    5303860