Municipal Residential Water Consumption Estimation Techniques Using Traditional and Soft Computing Approach: a Review

dc.contributor.authorSurendra, H.J.
dc.contributor.authorDeka, P.C.
dc.date.accessioned2026-02-05T13:17:26Z
dc.date.issued2022
dc.description.abstractRate of urbanization in towns and cities is so rapid, which leads to increase in the demand of water. Any developmental activities depend on availability of water. It is necessary to serve residents with better urban infrastructure by balancing both supply and demand. Hence, identifying the factors influencing consumption of water in residential area is very important. In this paper, climatic variables and socio-economic factors influencing water consumption and its computing techniques are discussed. Many studies showed that soft computing models are excellent models for predictions; however, they have been exiguously reported. Hence, here the advantages of soft computing methods are discussed and compared with traditional methods. In the present study, soft computing techniques and its applications such as fuzzy logic (FL), artificial neural network (ANN), adaptive neuro fuzzy inference system (ANFIS) and different wavelets are summarized and reviewed from problem point of view and application point of view. Several information on the possible future research, application and combinations using soft computing methods were discussed. © 2022, The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd.
dc.identifier.citationWater Conservation Science and Engineering, 2022, Vol.7, 1, p. 77-85
dc.identifier.issn23663340
dc.identifier.urihttps://doi.org/10.1007/s41101-022-00127-2
dc.identifier.urihttps://idr.nitk.ac.in/handle/123456789/28342
dc.publisherSpringer Science and Business Media B.V.
dc.subjectClimatic variables
dc.subjectDemand
dc.subjectSocio-economic factors
dc.subjectSoft computing techniques
dc.subjectWater consumption
dc.titleMunicipal Residential Water Consumption Estimation Techniques Using Traditional and Soft Computing Approach: a Review

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