Comparative evaluation of imperialist competitive algorithm and artificial neural networks for estimation of reservoirs storage capacity
Abstract Reservoirs provide rural and municipal water supply for various purposes such as drinking water, irrigation, hydropower, industrial purposes and recreational activities. Supplying these demands depends strongly on the dam reservoir capacity. Hence, reservoir storage capacity prediction is a...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
SpringerOpen
2020-06-01
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| Series: | Applied Water Science |
| Subjects: | |
| Online Access: | http://link.springer.com/article/10.1007/s13201-020-01259-3 |
| Summary: | Abstract Reservoirs provide rural and municipal water supply for various purposes such as drinking water, irrigation, hydropower, industrial purposes and recreational activities. Supplying these demands depends strongly on the dam reservoir capacity. Hence, reservoir storage capacity prediction is a determining factor in water resources planning and management, drought risk management, flood risk assessment and management. In the present study, imperialist competitive algorithm as a relatively new socio-political-based global search technique introduced for solving different optimization problems employed to predict reservoir storage capacity of Shaharchay dam located in the Urmia lake basin in northwest of Iran. The high convergence rate of imperialist competitive algorithm along with its capability in finding global optimal is striking aspect of the algorithm. The results obtained from this algorithm were compared with those of Artificial Neural Network. The comparison of the results with the measured ones by means of error measures indicates the superiority of imperialist competitive algorithm over Artificial Neural Network. |
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| ISSN: | 2190-5487 2190-5495 |