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Please use this identifier to cite or link to this item: http://dspace.bits-pilani.ac.in:8080/jspui/handle/123456789/15700
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dc.contributor.authorGupta, Rajiv-
dc.date.accessioned2024-09-24T16:41:56Z-
dc.date.available2024-09-24T16:41:56Z-
dc.date.issued2023-
dc.identifier.urihttps://ieeexplore.ieee.org/abstract/document/10129533/keywords#keywords-
dc.identifier.urihttp://dspace.bits-pilani.ac.in:8080/jspui/xmlui/handle/123456789/15700-
dc.description.abstractDry and semi-arid regions of the world witness a decrease in freshwater supply due to urbanization and population growth. Effective water utilization and management is the nexus at the consumer end for overcoming water scarcity. Limited research has yet concentrated on the end-user water study and its ideal solution, suggesting the necessity for research encompassing the end user s viewpoint for effective water management. The proposed study adopts a novel approach to determine the optimum daily per capita demand by implementing the Genetic algorithm (GA), an Artificial Intelligence (AI) tool. The multi-linear regression (MLR) model is applied to data from the socioeconomic household survey to perform the optimization. A household survey in the Jaipur Municipal Corporation region was conducted as a case study to validate the proposed study. Instead of the 133.66 LPCD specified by the regulating body, the executed optimization yields values from 106.62 to 131.52. The proposed methodology provides an alternate user perspective to minimize water wastage, which is further implemented with additional constraints.en_US
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.subjectCivil Engineeringen_US
dc.subjectGenetic Algorithm (GA)en_US
dc.subjectArtificial Intelligence (AI)en_US
dc.titleAn efficient urban water management practice based on optimum LPCD estimated using the MLR-GA optimization approach- A case study for Jaipur, Rajasthan (India)en_US
dc.typeArticleen_US
Appears in Collections:Department of Civil Engineering

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