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dc.creatorWang, Dong
dc.creatorSingh, Vijay P.
dc.creatorZhu, Yuansheng
dc.date.accessioned2011-03-30T17:08:37Z
dc.date.available2011-03-30T17:08:37Z
dc.date.issued2007-05-08
dc.identifier.citationWang, 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.issn0043-1397
dc.identifier.urihttp://dx.doi.org/10.1029/2006WR005490
dc.identifier.urihttp://hdl.handle.net/1969.1/94169
dc.descriptionAn edited version of this paper was published by AGU. Copyright 2007 American Geophysical Union.en_US
dc.description.abstractWater 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.sponsorshipThis project was supported by the Nanjing University Talent Development Foundation.en_US
dc.language.isoenen_US
dc.publisherAmerican Geological Unionen_US
dc.subjectengineering fuzzy set theoryen_US
dc.subjecteutrophicationen_US
dc.subjectevaluationen_US
dc.titleHybrid fuzzy and optimal modeling for water quality evaluationen_US
dc.typeArticleen_US
local.departmentCivil Engineeringen_US
local.departmentBiological and Agricultural Engineeringen_US


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