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Analysis of wave directional spreading using neural networks

DRS at CSIR-National Institute of Oceanography

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Title Analysis of wave directional spreading using neural networks
 
Creator Deo, M.C.
Gondane, D.S.
SanilKumar, V.
 
Subject wave direction
wave data
wave dispersion
wave energy
wave height
wave period
regression analysis
mathematical models
 
Description The short-term directional spreading of wave energy at a given location is popularly modeled with the help of the Cosine Power model. This model is oriented mainly around value of the spreading parameter involved in its expression. This paper describes how a representative spreading parameter could be arrived at from easily available wave parameters such as significant wave height and average zero-cross wave period, using the technique of neural networks. It is shown that training of the network with the help of observed directional wave (e.g., heave-pith-roll buoy) and could be used to establish dependency of the spreading parameter on more commonly available unidirectional wave parameters derived from, for example, pressure gauge data. It is found that such a procedure involving neural networks is much more accurate and reliable than the conventional approach based on statistical linear regression.
 
Date 2008-08-11T08:51:39Z
2008-08-11T08:51:39Z
2002
 
Type Journal Article
 
Identifier Journal of Waterway, Port, Coastal and Ocean Engineering, Vol. 128(1); 30-37p.
http://drs.nio.org/drs/handle/2264/1437
 
Language en
 
Rights ASCE
 
Publisher ASCE