Water Quality Evaluation Method Based on a T-S Fuzzy Neural Network—Application in Water Environment Trend Analysis of Taihu Lake Basin

In response to the problems of large computational volume and tedious computational process of fuzzy integrated evaluation, and general neural network models without clear water quality training criteria, this paper organically combines fuzzy rules, affiliation function, and neural network, and prop...

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Autores principales:	Wei Ye, Wei Song, Chen-Feng Cui, Jia-Hao Wen
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	water quality evaluation fuzzy integrated evaluation method T-S fuzzy neural network Taihu Lake Basin Hydraulic engineering TC1-978 Water supply for domestic and industrial purposes TD201-500
Acceso en línea:	https://doaj.org/article/4cd16a9af50047908ac79f09b7f3696a
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id	oai:doaj.org-article:4cd16a9af50047908ac79f09b7f3696a
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spelling	oai:doaj.org-article:4cd16a9af50047908ac79f09b7f3696a2021-11-11T19:58:11ZWater Quality Evaluation Method Based on a T-S Fuzzy Neural Network—Application in Water Environment Trend Analysis of Taihu Lake Basin10.3390/w132131272073-4441https://doaj.org/article/4cd16a9af50047908ac79f09b7f3696a2021-11-01T00:00:00Zhttps://www.mdpi.com/2073-4441/13/21/3127https://doaj.org/toc/2073-4441In response to the problems of large computational volume and tedious computational process of fuzzy integrated evaluation, and general neural network models without clear water quality training criteria, this paper organically combines fuzzy rules, affiliation function, and neural network, and proposes a comprehensive method for the evaluation of water quality based on a T-S fuzzy neural network. On the three water quality monitoring data of six national key monitoring stations in Taihu Lake Basin, three evaluation methods—the one-factor evaluation method, the fuzzy integrated evaluation method, and the T-S fuzzy neural network evaluation method—were used to comprehensively evaluate water environment quality, and the results showed that the T-S fuzzy neural network method has the advantages of convenient calculation, strong applicability, and scientific results.Wei YeWei SongChen-Feng CuiJia-Hao WenMDPI AGarticlewater quality evaluationfuzzy integrated evaluation methodT-S fuzzy neural networkTaihu Lake BasinHydraulic engineeringTC1-978Water supply for domestic and industrial purposesTD201-500ENWater, Vol 13, Iss 3127, p 3127 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	water quality evaluation fuzzy integrated evaluation method T-S fuzzy neural network Taihu Lake Basin Hydraulic engineering TC1-978 Water supply for domestic and industrial purposes TD201-500
spellingShingle	water quality evaluation fuzzy integrated evaluation method T-S fuzzy neural network Taihu Lake Basin Hydraulic engineering TC1-978 Water supply for domestic and industrial purposes TD201-500 Wei Ye Wei Song Chen-Feng Cui Jia-Hao Wen Water Quality Evaluation Method Based on a T-S Fuzzy Neural Network—Application in Water Environment Trend Analysis of Taihu Lake Basin
description	In response to the problems of large computational volume and tedious computational process of fuzzy integrated evaluation, and general neural network models without clear water quality training criteria, this paper organically combines fuzzy rules, affiliation function, and neural network, and proposes a comprehensive method for the evaluation of water quality based on a T-S fuzzy neural network. On the three water quality monitoring data of six national key monitoring stations in Taihu Lake Basin, three evaluation methods—the one-factor evaluation method, the fuzzy integrated evaluation method, and the T-S fuzzy neural network evaluation method—were used to comprehensively evaluate water environment quality, and the results showed that the T-S fuzzy neural network method has the advantages of convenient calculation, strong applicability, and scientific results.
format	article
author	Wei Ye Wei Song Chen-Feng Cui Jia-Hao Wen
author_facet	Wei Ye Wei Song Chen-Feng Cui Jia-Hao Wen
author_sort	Wei Ye
title	Water Quality Evaluation Method Based on a T-S Fuzzy Neural Network—Application in Water Environment Trend Analysis of Taihu Lake Basin
title_short	Water Quality Evaluation Method Based on a T-S Fuzzy Neural Network—Application in Water Environment Trend Analysis of Taihu Lake Basin
title_full	Water Quality Evaluation Method Based on a T-S Fuzzy Neural Network—Application in Water Environment Trend Analysis of Taihu Lake Basin
title_fullStr	Water Quality Evaluation Method Based on a T-S Fuzzy Neural Network—Application in Water Environment Trend Analysis of Taihu Lake Basin
title_full_unstemmed	Water Quality Evaluation Method Based on a T-S Fuzzy Neural Network—Application in Water Environment Trend Analysis of Taihu Lake Basin
title_sort	water quality evaluation method based on a t-s fuzzy neural network—application in water environment trend analysis of taihu lake basin
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/4cd16a9af50047908ac79f09b7f3696a
work_keys_str_mv	AT weiye waterqualityevaluationmethodbasedonatsfuzzyneuralnetworkapplicationinwaterenvironmenttrendanalysisoftaihulakebasin AT weisong waterqualityevaluationmethodbasedonatsfuzzyneuralnetworkapplicationinwaterenvironmenttrendanalysisoftaihulakebasin AT chenfengcui waterqualityevaluationmethodbasedonatsfuzzyneuralnetworkapplicationinwaterenvironmenttrendanalysisoftaihulakebasin AT jiahaowen waterqualityevaluationmethodbasedonatsfuzzyneuralnetworkapplicationinwaterenvironmenttrendanalysisoftaihulakebasin
_version_	1718431344950771712

Water Quality Evaluation Method Based on a T-S Fuzzy Neural Network—Application in Water Environment Trend Analysis of Taihu Lake Basin

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