Prediction and optimization of oscillating wave surge converter using machine learning techniques-Reference-Cited by-同舟云学术

Prediction and optimization of oscillating wave surge converter using machine learning techniques

Published:2020-04 Issue: Volume:210 Page:112677
ISSN:0196-8904
Container-title:Energy Conversion and Management
language:en
Short-container-title:Energy Conversion and Management

Author:

Liu Zhenqing,Wang Yize^ORCID,Hua Xugang

Funder

Research and Development

Publisher

Elsevier BV

Subject

Energy Engineering and Power Technology,Fuel Technology,Nuclear Energy and Engineering,Renewable Energy, Sustainability and the Environment

Reference72 articles.

1. Chow YC, Chang YC, Lin CC, Chen JH, Tzang SY. Experimental investigations on wave energy capture of two bottom-hinged-flap WECs operating in tandem. Ocean Eng 164 (2018) 322–331. doi: https://doi.org/10.101/j.oceaneng.2018.06.010.

2. Hydrodynamic response of the WEC sub-system of a novel hybrid wind-wave energy converter;Perez-Collazo;Energy Convers Manage,2018

3. Assessment of the power conversion of wave energy converters based on experimental tests;Rodríguez;Energy Convers Manage,2018

4. Hydrodynamic response and power efficiency analysis of heaving wave energy converter integrated with breakwater;Reabroy;Energy Convers Manage,2019

5. Optimizing ocean-wave energy extraction of a dual coaxial cylinder WEC using nonlinear model predictive control;Son;Appl Energy,2017

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