Banadkooki, Fatemeh Barzegari and Adamowski, Jan and Singh, Vijay P. and Ehteram, Mohammad and Karami, Hojat and Mousavi, Sayed Farhad and Farzin, Saeed and El-Shafie, Ahmed (2020) Crow algorithm for irrigation management: A case study. Water Resources Management, 34 (3). pp. 1021-1045. ISSN 0920-4741, DOI https://doi.org/10.1007/s11269-020-02488-6.
Full text not available from this repository.Abstract
This study employed a new evolutionary algorithm namely, the crow algorithm (CA), to optimize reservoir operation and minimize irrigation water deficit. Comprehensive analysis have been carried out between the proposed CA algorithm and other algorithms such as Prticle Swarm optimization (PSO), Shark Algorithm (SA), Genetic Algorithm (GA), and Weed Algorithm (WA). In addition, in order to select the optimal optimization algorithm among all of the investigated ones, a Multi-Criteria Decision model has been utilized. The time of computation was 45 s for CA but was 65, 50, 78, and 99 s for SA, WA, PSO, and GA, respectively. The CA exhibited greater volumetric reliability and a lower vulnerability index over the other examined algorithms. Furthermore, the Root Mean Square Error (RMSE) between demand and water release was 1.11 x 10(6) m(3) for CA compared to 2.14 x 10(6) m(3), 3.33 x 10(6) m(3), 3.45 x 10(6) m(3), and 3.78 x 10(6) m(3) for SA, WA, PSO, and GA, respectively. Using a multi-criteria decision model based on different indices, including the vulnerability index, resiliency index and volumetric reliability index, CA was ranked first.
| Item Type: | Article |
|---|---|
| Funders: | University of Malaya Research, GPF082A-2018, Universiti Malaya |
| Uncontrolled Keywords: | Crow algorithm; Water resources management; Reservoir operation; Irrigation management |
| Subjects: | T Technology > TC Hydraulic engineering. Ocean engineering T Technology > TD Environmental technology. Sanitary engineering |
| Divisions: | Faculty of Engineering > Department of Civil Engineering |
| Depositing User: | Ms Zaharah Ramly |
| Date Deposited: | 01 Dec 2023 05:05 |
| Last Modified: | 01 Dec 2023 05:05 |
| URI: | http://eprints.um.edu.my/id/eprint/36908 |
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