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https://dspace.univ-ouargla.dz/jspui/handle/123456789/25334
Title: | Streamflow prediction using a new approach of hybrid artificial neural network with discrete wavelet transform. A case study: the catchment of Seybouse in northeastern Algeria |
Authors: | TIKHAMARINE, Yazid SOUAG-GAMANE, Doudja MELLAK, Soumia CHERGUI, Sakina |
Keywords: | discrete wavelet transform Streamflow prediction artificial neural network Seybouse watershed |
Issue Date: | 16-Oct-2019 |
Publisher: | Université Kasdi Merbah Ouargla |
Abstract: | predicting streamflow values accurately is vitally important for hydrology and hydrogeology in water resources management system. Daily and monthly streamflow prediction can help in water management domain, regulation distribution of dams and estimation of groundwater level, especially in drought and flood issues. Streamflow forecast contributes to improve long and short-term time series by using previous information, therefore a power performance model should be used to process |
Description: | Séminaire International sur l′Hydrogéologie et l′Environnement SIHE 2019 Ouargla |
URI: | http://dspace.univ-ouargla.dz/jspui/handle/123456789/25334 |
Appears in Collections: | 4. Faculté des Hydrocarbures, des Energies Renouvelables, des Sciences de la Terre et de l’Univers |
Files in This Item:
File | Description | Size | Format | |
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TIKHAMARINE Yazid.pdf | 366,34 kB | Adobe PDF | View/Open |
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