NDLI: Improvement of Fuzzy Comprehensive Evaluation Model for Water Quality

Content Provider	IEEE Xplore Digital Library
Author	Nianpeng Wang Limin Liu Yanjun Pang
Copyright Year	2009
Abstract	Dimensionless method will make information distortion, and can not be controlled by information condition of water quality classification. Thus, theoretically, fuzzy recognition which takes “distance” as similarity measurement is not suitable for evaluating water quality, the best choice for which is to use membership degree as similarity measurement between sampling points and classes. However, fuzzy comprehensive evaluation based on membership degree exists the following problems:1) It is faulty to use “over standard weight” to realize the conversion of member ship degree from index value to sample point; 2) Fuzzy membership functions is not normal. Both of the problems cause undesirable results, and our improved methods be:1) Ruled fuzzy membership function and its properties, such as topological space structure, algebraic properties and normalized method; 2) Point out that the conversion of membership degree from index value to sample point is a pure mathematical problem and index distinguish weight be determined only by the entropy of index value membership degree. Finally, we take an example to analyze the improved method, and comparing with the results of same cases, we can observe the difference between the original method and the improved method in the paper.
Starting Page	534
Ending Page	538
File Size	312476
Page Count	5
File Format	PDF
ISBN	9780769537351
DOI	10.1109/FSKD.2009.503
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-08-14
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Knowledge engineering Fuzzy control Fuzzy sets Measurement standards Sampling methods Fuzzy neural networks Entropy Pattern recognition Distortion measurement Fuzzy systems
Content Type	Text
Resource Type	Article

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