• DocumentCode
    498973
  • Title

    Environmental quality comprehensive evaluation of tailing reservoir based on information entropy and fuzzy mathematics

  • Author

    Si, Chun-di ; En-Li Chen ; Wang, En-li Chen Cui-yan

  • Author_Institution
    Shijiazhuang Railway Inst., Shijiazhuang, China
  • Volume
    2
  • fYear
    2009
  • fDate
    12-15 July 2009
  • Firstpage
    625
  • Lastpage
    630
  • Abstract
    The environment of tailing reservoir greatly affects the environment around it. In this paper, a fuzzy analytic hierarchy process model is established to evaluate the environmental quality of tailing reservoir. By using of information entropy, a new weight calculation method which can evaluate the quality of information given by evaluation specialists is given, to amend the index subjective weight given by specialists through analytic hierarchy process. The expert scoring method is used to express the environmental quality of each evaluation index, finally the environmental quality situation of tailing reservoir is gained. A case study indicates that the environmental quality comprehensive evaluation model based on information entropy and fuzzy mathematics could deal with the uncertainty in the analytic process, the evaluation results are scientific and rational, thus a new way is provided to research on the environmental quality comprehensive evaluation of tailing reservoir.
  • Keywords
    decision making; decision theory; entropy; environmental factors; fuzzy set theory; reservoirs; environmental quality comprehensive evaluation index; expert scoring method; fuzzy analytic hierarchy process model; fuzzy mathematics; information entropy; tailing reservoir; weight calculation method; Cybernetics; Information analysis; Information entropy; Machine learning; Mathematical model; Mathematics; Reservoirs; Stability; Water pollution; Water resources; Environmental quality; Fuzzy comprehensive evaluation; Information entropy; Tailing reservoir;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Learning and Cybernetics, 2009 International Conference on
  • Conference_Location
    Baoding
  • Print_ISBN
    978-1-4244-3702-3
  • Electronic_ISBN
    978-1-4244-3703-0
  • Type

    conf

  • DOI
    10.1109/ICMLC.2009.5212395
  • Filename
    5212395