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...
Published in: | International Journal of River Basin Management |
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2016
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2-s2.0-84959047944 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 |
format |
Review |
accesstype |
|
record_format |
scopus |
collection |
Scopus |
_version_ |
1820775473409425408 |