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Volume 9, Issue 17 (9-2013)                   Marine Engineering 2013, 9(17): 77-86 | Back to browse issues page

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Sadeghifar T, Azarmsa S A, Vafakhah M. Prediction of Alongshore Sediment Transport Rate Using Semi-Empirical Formulas and an Artificial Neural Networks (ANNs) model in Noor Coastal zone . Marine Engineering 2013; 9 (17) :77-86
URL: http://marine-eng.ir/article-1-219-en.html
Prediction of Alongshore Sediment Transport Rate Using Semi-Empirical Formulas and an Artificial Neural Networks (ANNs) model in Noor Coastal zone
Tayeb Sadeghifar1 , Seyed Ali Azarmsa * 1, Mehdi Vafakhah1
1- Faculty of Marine Sciences, Tarbiat Modares University, Noor
Abstract:   (12464 Views)
Comparisons made between the measured data carried out from September to December 2012 using a streamer trap and the results of some semi-empirical formulas including C.E.R.C, Walton and Bruno (W.B), van der Meer (V), Kamphuis (K), and an Artificial Neural Network (ANN) model. Six dominant variables are considered in the ANN model to estimate long-shore sediment transport rate. Results reveal that among the semi-empirical formulas, Kamphuis formula has provided more reliable results than others and its %7 errors related to the observed data is partially resulted from the errors in input parameters. In contrast, the ANN model provides more accurate results with %6 error related to measured data and thus it is recommended to be applied in long-shore sediment transport rate estimation in similar research contexts.
Keywords: Sediment Transport, semi empirical Formula, Caspian Sea
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Type of Study: Research Paper | Subject: Main Engine & Electrical Equipments
Received: 2012/11/20 | Accepted: 2013/08/20
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