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
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