Ocean wave parameters estimation using backpropagation neural networks
DRS at CSIR-National Institute of Oceanography
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Title |
Ocean wave parameters estimation using backpropagation neural networks
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Creator |
Mandal, S.
SubbaRao Raju, D.H. |
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Subject |
surface water waves
wave spectra wave propagation correlation analysis wave parameters wave forecasting |
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Description |
In the present study, various ocean wave parameters are estimated from theoretical Pierson-Moskowitz spectra as well as measured ocean wave spectra using back propagation neural networks (BNN). Ocean wave parameters estimation by BNN shows that the correlations are very close to one. This substantiates the use of neural networks (NN). For Indian coast, Scott spectra are used as it reasonably represents the measured spectra. The correlations of NN and Scott spectra are also compared. Once the network is trained the ocean wave parameters can be estimated for unknown measured spectra, whereas significant wave height and spectral peak period are required to first generate the Scott spectra and then estimate other ocean wave parameters.
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Date |
2008-02-22T04:58:49Z
2008-02-22T04:58:49Z 2005 |
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Type |
Journal Article
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Identifier |
Marine structures, Vol.18; 301-318p.
http://drs.nio.org/drs/handle/2264/913 |
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Language |
en
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Rights |
Copyright [2005]. It is tried to respect the rights of the copyright holders to the best of the knowledge. If it is brought to our notice by copyright holder that the rights are voilated then the item would be withdrawn.
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Publisher |
Elsevier
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