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

عنوان مقاله: Utilizing artificial neural network to measure stream flow in flood plain (Case study: Sepidroud watershed)
شناسه ملی مقاله: IREC09_162
منتشر شده در نهمین سمینار بین المللی مهندسی رودخانه در سال 1391
مشخصات نویسندگان مقاله:

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

خلاصه مقاله:
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

کلمات کلیدی:
stream flow, neural network, water management, Sepidroud watershed

صفحه اختصاصی مقاله و دریافت فایل کامل: https://civilica.com/doc/186560/