Premium
A COMPLEMENTARY TOOL TO WATER QUALITY INDEX: FUZZY CLUSTERING ANALYSIS 1
Author(s) -
Kung Hsiangte,
Ying Longgen,
Liu YouCi
Publication year - 1992
Publication title -
jawra journal of the american water resources association
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.957
H-Index - 105
eISSN - 1752-1688
pISSN - 1093-474X
DOI - 10.1111/j.1752-1688.1992.tb03174.x
Subject(s) - data mining , fuzzy clustering , fuzzy logic , cluster analysis , computer science , complement (music) , relation (database) , fuzzy classification , chart , water quality , artificial intelligence , fuzzy set , mathematics , statistics , ecology , biochemistry , chemistry , complementation , biology , gene , phenotype
A general methodology for fuzzy clustering analysis is developed and illustrated with a case study of water quality evaluation for Dianshan Lake, Shanghai, China. Fuzzy clustering analysis may be used whenever a composite classification of water quality incorporates multiple parameters. In such cases, the technique may be used as a complement or an alternative to comprehensive assessment. In fuzzy clustering analysis, the classification is determined by a fuzzy relation. After a fuzzy similarity matrix has been established and the fuzzy relation stabilized, a dynamic clustering chart can be developed. Given a suitable threshold, the appropriate classification is worked out. The methodology is relatively simple, and the results can be interpreted to provide valuable information to support decision making and to aid water quality management.