• DocumentCode
    507249
  • Title

    Research on Forecasting Method of Urban Water Demand Based on Fuzzy Theory

  • Author

    Liu, Hongbo ; Deng, Tegang ; Zhang, Hongwei

  • Author_Institution
    Sch. of Environ. Sci. & Technol., Tianjin Univ., Tianjin, China
  • Volume
    6
  • fYear
    2009
  • fDate
    14-16 Aug. 2009
  • Firstpage
    389
  • Lastpage
    395
  • Abstract
    Water demand forecasting is very important in urban water supply management. A large number of researches have been done on water demand forecasting methods. In order to meet the easy operation and high accuracy requirements, a new forecasting method based on fuzzy theory, adaptive neuro-fuzzy inference system (ANFIS), was presented. The parameters of this method are obtained by the original fuzzy rules from the samples and optimized according to the latest history data based on adaptive mix learning arithmetic. At the same time, this forecasting system input variables are embodied the information, such as factors of burthen increasing, periodicity, the load changeable trends and the weather etc. The system configuration is very simple and valid. Based on imitated example, the consequence predicting precision of this method can satisfy the engineering request.
  • Keywords
    adaptive systems; demand forecasting; environmental management; fuzzy reasoning; fuzzy set theory; water resources; adaptive mix learning arithmetic; adaptive neuro-fuzzy inference system; fuzzy theory; urban water supply management; water demand forecasting; water demand forecasting method; Adaptive systems; Artificial neural networks; Autoregressive processes; Biological neural networks; Demand forecasting; Economic forecasting; Fuzzy systems; Partial response channels; Predictive models; Water resources; adaptive neuro-fuzzy inference system; fuzzy inference; fuzzy theory; water demand forecasting;
  • 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.2009.639
  • Filename
    5359875