Prediction of significant wave height; comparison between nested grid numerical model, and machine learning models of artificial neural networks, extreme learning and support vector machines

Prediction of significant wave height; comparison between nested grid numerical model, and machine learning models of artificial neural networks, extreme learning and support vector machines

Estimation of wave height is essential for several coastal engineering applications. This study advances a nested grid numerical model and compare its efficiency with three machine learning (ML) methods of artificial neural networks (ANN), extreme learning machines (ELM) and support vector regressio...

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Bibliographic Details
Main Authors: Shahaboddin Shamshirband, Amir Mosavi, Timon Rabczuk, Narjes Nabipour, Kwok-wing Chau
Format: Article
Language:English
Published: Taylor & Francis Group 2020-01-01
Series:Engineering Applications of Computational Fluid Mechanics
Subjects:
numerical modeling
nested grid
wind waves
machine learning
extreme learning machines
deep learning
Online Access:http://dx.doi.org/10.1080/19942060.2020.1773932

Internet

http://dx.doi.org/10.1080/19942060.2020.1773932

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