Comparison of artificial neural networks and autoregressive model for inflows forecasting of Roseires Reservoir for better prediction of irrigation water supply in Sudan-Reference-Cited by-同舟云学术

Comparison of artificial neural networks and autoregressive model for inflows forecasting of Roseires Reservoir for better prediction of irrigation water supply in Sudan

Published:2015-02-09 Issue:2 Volume:13 Page:203-214
ISSN:1571-5124
Container-title:International Journal of River Basin Management
language:en
Short-container-title:International Journal of River Basin Management

Author:

Abdellatif Mawada E.¹,Osman Yassin Z.²,Elkhidir Adil M.³

Affiliation:

1. Research Associate, School of the Built Environment, Liverpool John Moores University, Byrom Street, Liverpool L3 3AF, UK

2. Lecturer, Faculty of Advanced Engineering, University of Bolton, Deane Road, Bolton BL3 5AB, UK

3. Associate Professor, Department of Civil Engineering, Faculty of Engineering & Architecture, University of Khartoum, Khartoum, Sudan

Publisher

Informa UK Limited

Subject

Water Science and Technology

Link

https://www.tandfonline.com/doi/pdf/10.1080/15715124.2014.1003381

Reference28 articles.

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3. BCEOM, 1999. Abay Basin integrated master plan study. Main report Ministry of Water Resources, Addis Ababa, Phase two, Volume, Agriculture, 1–2.

4. Tools for the assessment of hydrological ensemble forecasts obtained by neural networks

5. A counterpropagation fuzzy-neural network modeling approach to real time streamflow prediction

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