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Sustainable management of water demand using fuzzy inference system: a case study of Kenyir Lake, Malaysia

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dc.citedby3
dc.contributor.authorMohd Azlan N.N.I.en_US
dc.contributor.authorAbdul Malek M.en_US
dc.contributor.authorZolkepli M.en_US
dc.contributor.authorMohd Salim J.en_US
dc.contributor.authorAhmed A.N.en_US
dc.contributor.authorid57221398340en_US
dc.contributor.authorid57221404206en_US
dc.contributor.authorid56429499300en_US
dc.contributor.authorid57221391747en_US
dc.contributor.authorid57214837520en_US
dc.date.accessioned2023-05-29T09:08:40Z
dc.date.available2023-05-29T09:08:40Z
dc.date.issued2021
dc.descriptionerror analysis; fuzzy mathematics; optimization; regression analysis; resource depletion; sustainability; water demand; water management; water resource; water stress; water use; Kenyir Lake; Malaysia; Terengganu; West Malaysia; ground water; water; fuzzy logic; human; lake; Malaysia; Fuzzy Logic; Groundwater; Humans; Lakes; Malaysia; Wateren_US
dc.description.abstractSustainable water demand management has become a necessity to the world since the immensely growing population and development have caused water deficit and groundwater depletion. This study aims to overcome water deficit by analyzing water demand at Kenyir Lake, Terengganu, using a fuzzy inference system (FIS). The analysis is widened by comparing FIS with the multiple linear regression (MLR) method. FIS applied as an analysis tool provides good generalization capability for optimum solutions and utilizes human behavior influenced by expert knowledge in water resources management for fuzzy rules specified in the system, whereas MLR can simultaneously adjust and compare several variables as per the needs of the study. The water demand dataset of Kenyir Lake was analyzed using FIS and MLR, resulting in total forecasted water consumptions at Kenyir Lake of 2314.38�m3 and 1358.22 m3, respectively. It is confirmed that both techniques converge close to the actual water consumption of 1249.98 m3. MLR showed the accuracy of the water demand values with smaller forecasted errors to be higher than FIS did. To attain sustainable water demand management, the techniques used can be examined extensively by researchers, educators, and learners by adding more variables, which will provide more anticipated outcomes. � 2021, The Author(s), under exclusive licence to Springer-Verlag GmbH, DE part of Springer Nature.en_US
dc.description.natureFinalen_US
dc.identifier.doi10.1007/s11356-020-11908-4
dc.identifier.epage20272
dc.identifier.issue16
dc.identifier.scopus2-s2.0-85099043270
dc.identifier.spage20261
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85099043270&doi=10.1007%2fs11356-020-11908-4&partnerID=40&md5=81d457f54575471f12faedc6c93bf1b2
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/26283
dc.identifier.volume28
dc.publisherSpringer Science and Business Media Deutschland GmbHen_US
dc.sourceScopus
dc.sourcetitleEnvironmental Science and Pollution Research
dc.titleSustainable management of water demand using fuzzy inference system: a case study of Kenyir Lake, Malaysiaen_US
dc.typeArticleen_US
dspace.entity.typePublication
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