Irrigation management based on reservoir operation with an improved weed algorithm
Irrigation; 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...
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2023
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my.uniten.dspace-237012023-05-29T14:51:06Z Irrigation management based on reservoir operation with an improved weed algorithm Ehteram M. Singh V.P. Karami H. Hosseini K. Dianatikhah M. Hossain M.S. Fai C.M. El-Shafie A. 57113510800 57211219633 36863982200 56153144500 57203893477 55579596900 57214146115 16068189400 Irrigation; 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]; Egypt Water 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. Final 2023-05-29T06:51:05Z 2023-05-29T06:51:05Z 2018 Article 10.3390/w10091267 2-s2.0-85053400275 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85053400275&doi=10.3390%2fw10091267&partnerID=40&md5=ad9aa62ffaadaac3e6426b9118d0d6ed https://irepository.uniten.edu.my/handle/123456789/23701 10 9 1267 All Open Access, Gold, Green MDPI AG Scopus |
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| description |
Irrigation; 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]; Egypt |
| author2 |
57113510800 |
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57113510800 Ehteram M. Singh V.P. Karami H. Hosseini K. Dianatikhah M. Hossain M.S. Fai C.M. El-Shafie A. |
| format |
Article |
| author |
Ehteram M. Singh V.P. Karami H. Hosseini K. Dianatikhah M. Hossain M.S. Fai C.M. El-Shafie A. |
| spellingShingle |
Ehteram M. Singh V.P. Karami H. Hosseini K. Dianatikhah M. Hossain M.S. Fai C.M. El-Shafie A. Irrigation management based on reservoir operation with an improved weed algorithm |
| author_sort |
Ehteram M. |
| title |
Irrigation management based on reservoir operation with an improved weed algorithm |
| title_short |
Irrigation management based on reservoir operation with an improved weed algorithm |
| title_full |
Irrigation management based on reservoir operation with an improved weed algorithm |
| title_fullStr |
Irrigation management based on reservoir operation with an improved weed algorithm |
| title_full_unstemmed |
Irrigation management based on reservoir operation with an improved weed algorithm |
| title_sort |
irrigation management based on reservoir operation with an improved weed algorithm |
| publisher |
MDPI AG |
| publishDate |
2023 |
| _version_ |
1806427611758329856 |
| score |
13.211869 |