ORCID Profile
0000-0002-3505-0759
Current Organisation
University of Kirkuk
Does something not look right? The information on this page has been harvested from data sources that may not be up to date. We continue to work with information providers to improve coverage and quality. To report an issue, use the Feedback Form.
Publisher: IWA Publishing
Date: 02-2009
DOI: 10.2166/NH.2009.012
Abstract: A hybrid model for streamflow generation is presented to explore the possibilities of using the multilayer feedforward artificial neural networks (ANNs) as generators of future scenarios, with emphasis on the ability to reproduce the statistics of flows related to drought and storage. The artificial neural network model has two components: deterministic and random. The second part of the model incorporates the uncertainty associated with the hydrological processes. The model is applied to the monthly inflows of Mula irrigation project in Maharashtra, India. A comparison of drought and storage among other statistics was made between the performance of the ANN-based model results and the results of the Thomas–Fiering models. The results show that ANN is a promising alternative modelling approach for flow simulation purposes, with interesting potential in the context of water resources systems management and optimization.
Publisher: Springer Science and Business Media LLC
Date: 06-04-2017
Publisher: Springer Science and Business Media LLC
Date: 28-01-2014
Publisher: Springer Science and Business Media LLC
Date: 19-03-2020
Publisher: Informa UK Limited
Date: 10-06-2019
Publisher: Elsevier BV
Date: 09-2020
Publisher: American Society of Civil Engineers (ASCE)
Date: 11-2009
No related grants have been discovered for Taymoor Awchi.