Please use this identifier to cite or link to this item:
Title: Artificial neural networks for estimation of temporal rate coefficient of equilibrium bar volume
Authors: Kankal, Murat
Kömürcü, Murat İhsan
Yüksek, Ömer
Akpınar, Adem
Keywords: Coastal Profiles;Artificial Neural Network;Temporal Variation;Bar Volume;Sediment Transport
Issue Date: Feb-2012
Publisher: NISCAIR-CSIR, India
Abstract: Present study consists the growth of a bar profile caused by cross-shore sediment transport. This is especially on growth of bar volume (V) toward equilibrium bar volume (Veq). Three analysis methods being a power and linear regression analysis (PRA and LRA) and an Artificial Neural Network (ANN) analysis were performed to determine empirical temporal rate coefficient (α). Forty-two experimental data were used for training set and the rest of the experimental data were used for testing set in the ANN analysis. As the results of analyses, the smallest average relative and root mean square error (RMSE) computed for the ANN methods are 7.578% and 0.029, respectively. It has been obtained that the ANN analysis, which is used for determination of α coefficient, gives reasonable results. Finally, bar volumes were calculated by means of computed α values and compared with the results of experimental data.
Page(s): 45-55
ISSN: 0975-1033 (Online); 0379-5136 (Print)
Appears in Collections:IJMS Vol.41(1) [February 2012]

Files in This Item:
File Description SizeFormat 
IJMS 41(1) 45-55.pdf345.37 kBAdobe PDFView/Open

Items in NOPR are protected by copyright, with all rights reserved, unless otherwise indicated.