Using fuzzy theory and information entropy for water quality assessment in Three Gorges region, China

  • Authors:

  • Li Liu;Jianzhong Zhou;Xueli An;Yongchuan Zhang;Li Yang

  • Affiliations:

  • College of Hydroelectric and Digitalization Engineering, Huazhong University of Science and Technology, Hubei Province, 430074 Wuhan, China;Dispatch & Communication Center, Hunan Electric Power Company, Hunan Province, Changsha 410007, China;State Key Laboratory of Control and Simulation of Power System and Generation Equipment, Department of Thermal Engineering, Tsinghua University, Beijing 100084, China;Dispatch & Communication Center, Hunan Electric Power Company, Hunan Province, Changsha 410007, China;Dispatch & Communication Center, Hunan Electric Power Company, Hunan Province, Changsha 410007, China

  • Venue:
  • Expert Systems with Applications: An International Journal
  • Year:
  • 2010

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Abstract

Considering that the water quality assessment is a fuzzy concept with multiple indicators and classes, and there are still some limits of fuzzy comprehensive evaluation method, the fuzzy mathematics method and the information entropy theory are combined to establish an improved fuzzy comprehensive evaluation method for water quality assessment. In this method, the exponential membership function has been adopted to solve the zero-weight problem, and the information entropy has been used to modify the coefficients of weight in order to exploit the useful information of data to a maximum extent. In addition, the weighted average principle has been taken to replace the maximum membership principle for reserving the information in the assessment coefficients as much as possible. The water quality of Three Gorges region is taken as an example and the results show that the improved fuzzy comprehensive evaluation method is superior to the traditional model and worth to be recommended.