Premium
Hybrid fuzzy and optimal modeling for water quality evaluation
Author(s) -
Wang Dong,
Singh Vijay P.,
Zhu Yuansheng
Publication year - 2007
Publication title -
water resources research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.863
H-Index - 217
eISSN - 1944-7973
pISSN - 0043-1397
DOI - 10.1029/2006wr005490
Subject(s) - randomness , fuzzy logic , entropy (arrow of time) , mathematical optimization , set (abstract data type) , fuzzy set , computer science , water quality , quality (philosophy) , principle of maximum entropy , data mining , mathematics , artificial intelligence , statistics , ecology , philosophy , physics , epistemology , quantum mechanics , biology , programming language
Water quality evaluation entails both randomness and fuzziness. Two hybrid models are developed, based on the principle of maximum entropy (POME) and engineering fuzzy set theory (EFST). Generalized weighted distances are defined for considering both randomness and fuzziness. The models are applied to 12 lakes and reservoirs in China, and their eutrophic level is determined. The results show that the proposed models are effective tools for generating a set of realistic and flexible optimal solutions for complicated water quality evaluation issues. In addition, the proposed models are flexible and adaptable for diagnosing the eutrophic status.