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Irrigation management based on reservoir operation with an improved weed algorithm

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dc.citedby14
dc.contributor.authorEhteram M.en_US
dc.contributor.authorSingh V.P.en_US
dc.contributor.authorKarami H.en_US
dc.contributor.authorHosseini K.en_US
dc.contributor.authorDianatikhah M.en_US
dc.contributor.authorHossain M.S.en_US
dc.contributor.authorFai C.M.en_US
dc.contributor.authorEl-Shafie A.en_US
dc.contributor.authorid57113510800en_US
dc.contributor.authorid57211219633en_US
dc.contributor.authorid36863982200en_US
dc.contributor.authorid56153144500en_US
dc.contributor.authorid57203893477en_US
dc.contributor.authorid55579596900en_US
dc.contributor.authorid57214146115en_US
dc.contributor.authorid16068189400en_US
dc.date.accessioned2023-05-29T06:51:05Z
dc.date.available2023-05-29T06:51:05Z
dc.date.issued2018
dc.descriptionIrrigation; Particle swarm optimization (PSO); Problem solving; Reservoir management; Reservoirs (water); Water resources; Agricultural productions; Computational time; High dams; Improved particle swarm optimization algorithms; Irrigation management; Objective functions; Reservoir operation; Water resources management; Genetic algorithms; agricultural production; algorithm; exploration; genetic algorithm; inflow; irrigation system; reservoir; resource management; water demand; water resource; Aswan Dam; Aswan [Egypt]; Egypten_US
dc.description.abstractWater scarcity is a serious problem throughout the world. One critical part of this problem is supplying sufficient water to meet irrigation demands for agricultural production. The present study introduced an improved weed algorithm for reservoir operation with the aim of decreasing irrigation deficits. The Aswan High Dam, one of the most important dams in Egypt, was selected for this study to supply irrigation demands. The improved weed algorithm (IWA) had developed local search ability so that the exploration ability for the IWA increased and it could escape from local optima. Three inflows (low, medium and high) to the reservoir were considered for the downstream demands. For example, the average solution for the IWA at high inflow was 0.985 while it was 1.037, 1.040, 1.115 and 1.121 for the weed algorithm (WA), bat algorithm (BA), improved particle swarm optimization algorithm (IPSOA) and genetic algorithm (GA). This meant that the IWA decreased the objective function for high inflow by 5.01%, 5.20%, 11.65% and 12% compared to the WA, BA, IPSOA and GA, respectively. The computational time for the IWA at high inflow was 22 s, which was 12%, 18%, 24% and 29% lower than the WA, BA, IPSOA and GA, respectively. Results indicated that the IWA could meet the demands at all three inflows. The reliability index for the IWA for the three inflows was greater than the WA, BA, IPSOA and GA, meaning that the released water based on IWA could well supply the downstream demands. Thus, the improved weed algorithm is suggested for solving complex problems in water resources management. � 2018 by the authors.en_US
dc.description.natureFinalen_US
dc.identifier.ArtNo1267
dc.identifier.doi10.3390/w10091267
dc.identifier.issue9
dc.identifier.scopus2-s2.0-85053400275
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85053400275&doi=10.3390%2fw10091267&partnerID=40&md5=ad9aa62ffaadaac3e6426b9118d0d6ed
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/23701
dc.identifier.volume10
dc.publisherMDPI AGen_US
dc.relation.ispartofAll Open Access, Gold, Green
dc.sourceScopus
dc.sourcetitleWater (Switzerland)
dc.titleIrrigation management based on reservoir operation with an improved weed algorithmen_US
dc.typeArticleen_US
dspace.entity.typePublication
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