Ocean wave parameters estimation using backpropagation neural networks

dc.contributor.authorMandal, S.
dc.contributor.authorRao, S.
dc.contributor.authorRaju, D.H.
dc.date.accessioned2020-03-31T08:39:01Z
dc.date.available2020-03-31T08:39:01Z
dc.date.issued2005
dc.description.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. 2005 Elsevier Ltd. All rights reserved.en_US
dc.identifier.citationMarine Structures, 2005, Vol.18, 3, pp.301-318en_US
dc.identifier.urihttps://idr.nitk.ac.in/handle/123456789/12339
dc.titleOcean wave parameters estimation using backpropagation neural networksen_US
dc.typeArticleen_US

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