Development of a novel hybrid optimization algorithm for minimizing irrigation deficiencies
computer system; dam; genetic algorithm; irrigation system; optimization; particle size; water management; Chondrichthyes
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my.uniten.dspace-247082023-05-29T15:26:06Z Development of a novel hybrid optimization algorithm for minimizing irrigation deficiencies Valikhan-Anaraki M. Mousavi S.-F. Farzin S. Karami H. Ehteram M. Kisi O. Fai C.M. Hossain M.S. Hayder G. Ahmed A.N. El-Shafie A.H. Bin Hashim H. Afan H.A. Lai S.H. El-Shafie A. 57209237974 7003344568 55315758000 36863982200 57113510800 6507051085 57214146115 55579596900 56239664100 57214837520 57207789882 56800153400 56436626600 36102664300 16068189400 computer system; dam; genetic algorithm; irrigation system; optimization; particle size; water management; Chondrichthyes One of the most important issues in the field of water resource management is the optimal utilization of dam reservoirs. In the current study, the optimal utilization of the Aydoghmoush Dam Reservoir is examined based on a hybrid of the bat algorithm (BA) and particle swarm optimization algorithm (PSOA) by increasing the convergence rate of the new hybrid algorithm (HA) without being trapped in the local optima. The main goal of the study was to reduce irrigation deficiencies downstream of this reservoir. The results showed that the HA reduced the computational time and increased the convergence rate. The average downstream irrigation demand over a 10-year period (1991-2000) was 25.12 � 106 m3, while the amount of water release based on the HA was 24.48 � 106 m3. Therefore, the HA was able to meet the irrigation demands better than some other evolutionary algorithms. Moreover, lower indices of root mean square error (RMSE) and mean absolute error (MAE) were obtained for the HA. In addition, a multicriteria decision-making model based on the vulnerability, reliability, and reversibility indices and the objective function performed better with the new HA than with the BA, PSOA, genetic algorithm (GA), and shark algorithm (SA) in terms of providing for downstream irrigation demands. � 2019 by the authors. Final 2023-05-29T07:26:06Z 2023-05-29T07:26:06Z 2019 Article 10.3390/su11082337 2-s2.0-85066942200 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85066942200&doi=10.3390%2fsu11082337&partnerID=40&md5=667a404a1d226b4403320de9119c0fc6 https://irepository.uniten.edu.my/handle/123456789/24708 11 8 2337 All Open Access, Gold, Green MDPI Scopus |
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computer system; dam; genetic algorithm; irrigation system; optimization; particle size; water management; Chondrichthyes |
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57209237974 Valikhan-Anaraki M. Mousavi S.-F. Farzin S. Karami H. Ehteram M. Kisi O. Fai C.M. Hossain M.S. Hayder G. Ahmed A.N. El-Shafie A.H. Bin Hashim H. Afan H.A. Lai S.H. El-Shafie A. |
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Article |
| author |
Valikhan-Anaraki M. Mousavi S.-F. Farzin S. Karami H. Ehteram M. Kisi O. Fai C.M. Hossain M.S. Hayder G. Ahmed A.N. El-Shafie A.H. Bin Hashim H. Afan H.A. Lai S.H. El-Shafie A. |
| spellingShingle |
Valikhan-Anaraki M. Mousavi S.-F. Farzin S. Karami H. Ehteram M. Kisi O. Fai C.M. Hossain M.S. Hayder G. Ahmed A.N. El-Shafie A.H. Bin Hashim H. Afan H.A. Lai S.H. El-Shafie A. Development of a novel hybrid optimization algorithm for minimizing irrigation deficiencies |
| author_sort |
Valikhan-Anaraki M. |
| title |
Development of a novel hybrid optimization algorithm for minimizing irrigation deficiencies |
| title_short |
Development of a novel hybrid optimization algorithm for minimizing irrigation deficiencies |
| title_full |
Development of a novel hybrid optimization algorithm for minimizing irrigation deficiencies |
| title_fullStr |
Development of a novel hybrid optimization algorithm for minimizing irrigation deficiencies |
| title_full_unstemmed |
Development of a novel hybrid optimization algorithm for minimizing irrigation deficiencies |
| title_sort |
development of a novel hybrid optimization algorithm for minimizing irrigation deficiencies |
| publisher |
MDPI |
| publishDate |
2023 |
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1806424251313422336 |