• DocumentCode
    2742381
  • Title

    A Forecast Model of Hydrologic Single Element Medium and Long-Period Based on Rough Set Theory

  • Author

    Sihui, Dong

  • Author_Institution
    Sch. of Civil & Safety Eng., Dalian Jiaotong Univ., Dalian, China
  • Volume
    1
  • fYear
    2009
  • fDate
    14-16 Aug. 2009
  • Firstpage
    19
  • Lastpage
    25
  • Abstract
    Based on rough set theory, this paper presents the single element medium and long-term classification forecast model which uses historical data of a hydrologic series as forecast factors. The minimal rule set, i.e., forecast pattern set, is achieved according to the principle of maximal attribute significance and rules frequency. Maximal support strength is put forward and applied to predict by using the model. The model is applied to forecast annual runoff of Dahuofang reservoir. The result indicates that the forecast model based on rough set can describe the relationship between forecast factors and forecast object efficiently and accurately. The model, which is composed of simple solution rules, is easily understood and applied.
  • Keywords
    forecasting theory; geophysics computing; hydrological techniques; hydrology; modelling; reservoirs; rough set theory; China; Dahuofang reservoir; annual runoff forecasting; forecast factors; forecast pattern set; hydrologic historical data; long term classification forecast model; maximal attribute significance principle; minimal rule set; rough set theory; rule frequency; single element medium forecast model; Data engineering; Extrapolation; Extraterrestrial measurements; Fuzzy reasoning; Fuzzy systems; Information analysis; Predictive models; Safety; Set theory; Weather forecasting; attribute significance; forecast model; hydrology; medium and long-term forecasts; rough set; single element; support strength;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Fuzzy Systems and Knowledge Discovery, 2009. FSKD '09. Sixth International Conference on
  • Conference_Location
    Tianjin
  • Print_ISBN
    978-0-7695-3735-1
  • Type

    conf

  • DOI
    10.1109/FSKD.2009.356
  • Filename
    5358670