| Autor: |
Bouzeria Housseyn, Ghenim Abderrahmane N., Khanchoul Kamel |
| Jazyk: |
angličtina |
| Rok vydání: |
2017 |
| Předmět: |
|
| Zdroj: |
Journal of Water and Land Development, Vol 33, Iss 1, Pp 47-55 (2017) |
| Druh dokumentu: |
article |
| ISSN: |
2083-4535 |
| DOI: |
10.1515/jwld-2017-0018 |
| Popis: |
In this study, we present the performances of the best training algorithm in Multilayer Perceptron (MLP) neural networks for prediction of suspended sediment discharges in Mellah catchment. Time series data of daily suspended sediment discharge and water discharge from the gauging station of Bouchegouf were used for training and testing the networks. A number of statistical parameters, i.e. root mean square error (RMSE), mean absolute error (MAE), coefficient of efficiency (CE) and coefficient of determination (R2) were used for performance evaluation of the model. The model produced satisfactory results and showed a very good agreement between the predicted and observed data. The results also showed that the performance of the MLP model was capable to capture the exact pattern of the sediment discharge data in the Mellah catchment. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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