Development of river water quality management using fuzzy techniques: a review

Fuzzy theory is a powerful tool with the capability of solving many complex problems which include river water quality assessment when dealing with uncertainties data and vagueness that occur in a river system. In this paper, various fuzzy techniques are applied in the development of river water qua...

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Published in:International Journal of River Basin Management
Main Author: Che Osmi S.F.; Malek M.A.; Yusoff M.; Azman N.H.; Faizal W.M.
Format: Review
Language:English
Published: Taylor and Francis Ltd. 2016
Online Access:https://www.scopus.com/inward/record.uri?eid=2-s2.0-84959047944&doi=10.1080%2f15715124.2015.1105232&partnerID=40&md5=2942d3757c04e7e8cc52692b0aedfb82
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Che Osmi S.F.; Malek M.A.; Yusoff M.; Azman N.H.; Faizal W.M.
Development of river water quality management using fuzzy techniques: a review
2016
International Journal of River Basin Management
14
2
10.1080/15715124.2015.1105232
https://www.scopus.com/inward/record.uri?eid=2-s2.0-84959047944&doi=10.1080%2f15715124.2015.1105232&partnerID=40&md5=2942d3757c04e7e8cc52692b0aedfb82
Fuzzy theory is a powerful tool with the capability of solving many complex problems which include river water quality assessment when dealing with uncertainties data and vagueness that occur in a river system. In this paper, various fuzzy techniques are applied in the development of river water quality management; particularly, water quality index assessment is outlined. Uncertainties involved in river water quality management, especially from random nature of hydrologic variables and missing data, can be overcome using fuzzy techniques. Fuzzy interference system (FIS) plays an important role in fuzzy excursion. FIS can be improved using other methods such as similarity measures and grey clustering method to obtain better and accurate water quality assessment results. FIS can also be integrated with an expert system and a decision support system to assist the decision-maker in improving river water quality through effective strategies. Thus, the capability of FIS to be incorporated with other techniques such as grey clustering, artificial neural network, and expert system to provide a comprehensive solution in order to control river pollution is demonstrated. © 2015 International Association for Hydro-Environment Engineering and Research.
Taylor and Francis Ltd.
15715124
English
Review

author Che Osmi S.F.; Malek M.A.; Yusoff M.; Azman N.H.; Faizal W.M.
spellingShingle Che Osmi S.F.; Malek M.A.; Yusoff M.; Azman N.H.; Faizal W.M.
Development of river water quality management using fuzzy techniques: a review
author_facet Che Osmi S.F.; Malek M.A.; Yusoff M.; Azman N.H.; Faizal W.M.
author_sort Che Osmi S.F.; Malek M.A.; Yusoff M.; Azman N.H.; Faizal W.M.
title Development of river water quality management using fuzzy techniques: a review
title_short Development of river water quality management using fuzzy techniques: a review
title_full Development of river water quality management using fuzzy techniques: a review
title_fullStr Development of river water quality management using fuzzy techniques: a review
title_full_unstemmed Development of river water quality management using fuzzy techniques: a review
title_sort Development of river water quality management using fuzzy techniques: a review
publishDate 2016
container_title International Journal of River Basin Management
container_volume 14
container_issue 2
doi_str_mv 10.1080/15715124.2015.1105232
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-84959047944&doi=10.1080%2f15715124.2015.1105232&partnerID=40&md5=2942d3757c04e7e8cc52692b0aedfb82
description Fuzzy theory is a powerful tool with the capability of solving many complex problems which include river water quality assessment when dealing with uncertainties data and vagueness that occur in a river system. In this paper, various fuzzy techniques are applied in the development of river water quality management; particularly, water quality index assessment is outlined. Uncertainties involved in river water quality management, especially from random nature of hydrologic variables and missing data, can be overcome using fuzzy techniques. Fuzzy interference system (FIS) plays an important role in fuzzy excursion. FIS can be improved using other methods such as similarity measures and grey clustering method to obtain better and accurate water quality assessment results. FIS can also be integrated with an expert system and a decision support system to assist the decision-maker in improving river water quality through effective strategies. Thus, the capability of FIS to be incorporated with other techniques such as grey clustering, artificial neural network, and expert system to provide a comprehensive solution in order to control river pollution is demonstrated. © 2015 International Association for Hydro-Environment Engineering and Research.
publisher Taylor and Francis Ltd.
issn 15715124
language English
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