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title

Utilizing artificial neural network to measure stream flow in flood plain (Case study: Sepidroud watershed)

Credit to Download: 1 | Page Numbers 6 | Abstract Views: 813
Year: 2012
Present: پوستر
COI code: IREC09_162
Paper Language: English

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Authors Utilizing artificial neural network to measure stream flow in flood plain (Case study: Sepidroud watershed)

  Alireza Mardookhpour - Ph.D.Department of Civil and Water Engineering,Lahijan Branch, Islamic Azad University
  Freydoon Godarzvand Chegini - B.S. Department of Water Engineering, Lahijan Branch, Islamic Azad University, Lahijan

Abstract:

In this paper, stream flow forecasting in long term series of time, has been investigated by ANN model. For knowing the hydrological behavior and water management of Sepidroud River (North of Iran-Gilan) the present study focused on stream flow forecasting with artificial neural network. Ten years (2000-2009) historical inflow data, observed from the Sepidroud River, were selected ; then 10 years inflow of the Sepidroud River have been forecasted by neural network. Finally, the results obtained from forecasted data compared with observed data. The results showed that neural network could predict stream flow with high precision and the maximum error between predicted and observed data was 3% approximately

Keywords:

stream flow, neural network, water management, Sepidroud watershed

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https://www.civilica.com/Paper-IREC09-IREC09_162.html
COI code: IREC09_162

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Mardookhpour, Alireza & Freydoon Godarzvand Chegini, 2012, Utilizing artificial neural network to measure stream flow in flood plain (Case study: Sepidroud watershed), 09th International River Engineering Conference, اهواز, دانشگاه شهيد چمران اهواز, https://www.civilica.com/Paper-IREC09-IREC09_162.htmlInside the text, wherever referred to or an achievement of this article is mentioned, after mentioning the article, inside the parental, the following specifications are written.
First Time: (Mardookhpour, Alireza & Freydoon Godarzvand Chegini, 2012)
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Type: Azad University
Paper No.: 2456
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