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River flow model using artificial neural networks
| Content Provider | Semantic Scholar |
|---|---|
| Author | Ia, Imen A. I. C. H. O. U. R. Ib, Azzedine H. A. N. Ab, Nabil B. O. U. G. H. E. R. I. R. Ib, Larbi D. J. A. B. R. Ib, Hicham C. H. A. F. F. A. Mc, Sami L. A. L. L. A. H. E. |
| Copyright Year | 2016 |
| Abstract | The use of artificial neural networks (ANNs) is becoming increasingly common in the analysis of hydrology and water resources problems. In this research, an ANN was developed and used to model the rainfall-runoff relationship, in a catchment located in a semiarid and Mediterranean climate in Algeria. The performance of the developed neural network-based model was compared against multiple linear regression-based models using the same observed data. It was found that the neural network model consistently gives superior predictions. Based on the results of this research, artificial neural network modeling appears to be a promising technique for the prediction of flow for catchments in semi-arid and Mediterranean regions. Accordingly, the neural network method can be applied to various hydrological systems where other models may be inappropriate. © 2015 The Authors. Published by Elsevier Ltd. Peer-review under responsibility of the Euro-Mediterranean Institute for Sustainable Development (EUMISD). |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | http://isiarticles.com/bundles/Article/pre/pdf/52479.pdf |
| Language | English |
| Access Restriction | Open |
| Subject Keyword | Artificial neural network Euro currency Hydrology Network model Regression Analysis Scientific Publication Semiconductor industry TYPSET and RUNOFF |
| Content Type | Text |
| Resource Type | Article |
