Significant wave height and energy flux estimation with a Genetic Fuzzy System for regression-Reference-Cited by-同舟云学术

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Significant wave height and energy flux estimation with a Genetic Fuzzy System for regression

Published:2018-07 Issue: Volume:160 Page:33-44
ISSN:0029-8018
Container-title:Ocean Engineering
language:en
Short-container-title:Ocean Engineering

Author:

Cornejo-Bueno L.,Rodríguez-Mier P.,Mucientes M.,Nieto-Borge J.C.,Salcedo-Sanz S.

Funder

FEDER

Spanish Ministerial Commission of Science and Technology

Comunidad Autónoma de Madrid under project

Consellería de Cultura, Educación e Ordenación Universitaria

European Regional Development

DAMA

Publisher

Elsevier BV

Subject

Ocean Engineering,Environmental Engineering

Reference45 articles.

1. Wave parameter estimation using neural networks;Agrawal;Mar. Struct.,2004

2. A Hybrid Genetic Algorithm – Extreme Learning Machine approach for accurate significant wave height reconstruction;Alexandre;Ocean. Model.,2015

3. Atlas of global wave energy from 10 years of reanalysis and hindcast data;Arinaga;Renew. Energy,2012

4. Generating electricity from the oceans;Bahaj;Renew. Sustain. Energy Rev.,2011

5. Wave energy resource characterization of the Atlantic marine energy test site;Cahill;Int. J. Mar. Energy,2013

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