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Hybrid fuzzy and optimal modeling for water quality evaluation

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dc.creator Wang, Dong
dc.creator Singh, Vijay P.
dc.creator Zhu, Yuansheng
dc.date.accessioned 2011-03-30T17:08:37Z
dc.date.available 2011-03-30T17:08:37Z
dc.date.issued 2007-05-08
dc.identifier.citation Wang, D., V. P. Singh, and Y. Zhu (2007), Hybrid fuzzy and optimal modeling for water quality evaluation, Water Resources Researc, 43, doi:10.1029/2006WR005490. To view the published open abstract, go to http://dx.doi.org and enter the DOI. en_US
dc.identifier.issn 0043-1397
dc.identifier.uri http://dx.doi.org/10.1029/2006WR005490
dc.identifier.uri http://hdl.handle.net/1969.1/94169
dc.description An edited version of this paper was published by AGU. Copyright 2007 American Geophysical Union. en_US
dc.description.abstract 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. en_US
dc.description.sponsorship This project was supported by the Nanjing University Talent Development Foundation. en_US
dc.language.iso en en_US
dc.publisher American Geological Union en_US
dc.subject engineering fuzzy set theory en_US
dc.subject eutrophication en_US
dc.subject evaluation en_US
dc.title Hybrid fuzzy and optimal modeling for water quality evaluation en_US
dc.type Article en_US
local.department Civil Engineering en_US
local.department Biological and Agricultural Engineering en_US

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