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Ocean wave parameters estimation using backpropagation neural networks
AbstractIn the present study, various ocean wave parameters are estimated from theoretical Pierson–Moskowitz spectra as well as measured ocean wave spectra using backpropagation 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.
Ocean wave parameters estimation using backpropagation neural networks
AbstractIn the present study, various ocean wave parameters are estimated from theoretical Pierson–Moskowitz spectra as well as measured ocean wave spectra using backpropagation 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.
Ocean wave parameters estimation using backpropagation neural networks
Mandal, S. (author) / Rao, Subba (author) / Raju, D.H. (author)
Marine Structures ; 18 ; 301-318
2005-09-22
18 pages
Article (Journal)
Electronic Resource
English
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