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You are here : eLibrary : IAHR World Congress Proceedings : 36th Congress - The Hague (2015) ALL CONTENT : Sediment management and morphodynamics : Artificial neural network modeling of suspended load inside surf zone using wavelet transform
Artificial neural network modeling of suspended load inside surf zone using wavelet transform
An artificial neural network (ANN) model is developed to predict the sediment suspension load at a specific time using
the components of different scales that have been extracted from the wavelet analysis of wave surface elevation data.
Considering that the period of each wave in a wave group can be detected by the wavelet transform of the surface
elevation data, a time series of each component from the analysis with a scale a is chosen to be an input data of the
ANN model if it passes through the local maximum which can be noted by (a,t) in a time- scale domain. The developed
model is used to predict the time-dependent sediment concentration data collected during the CROSSTEX (CROss-
Shore Sediment Transport EXperiment) at Oregon State University. The peak wave period was 4 s for the erosive case
and 6.8 s for the accretive case.
File Size : 575,132 bytes
File Type : Adobe Acrobat Document
Chapter : IAHR World Congress Proceedings
Category : 36th Congress - The Hague (2015) ALL CONTENT
Article : Sediment management and morphodynamics
Date Published : 28/08/2015
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