Neural networks for estimation of ocean wave parameters
Abstract
Ocean wave parameters play a significant role in the design of all coastal and offshore structures. In the present study, neural networks are used to estimate various ocean wave parameters from theoretical Pierson-Moskowitz spectra as well as measured ocean wave spectra off Mormugao, west coast of India. The correlations of neural network 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 generate the Scott spectra. This study shows that the missing field wave data can be generated using trained network.
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