Short-term wave power forecasting with hybrid multivariate variational mode decomposition model integrated with cascaded feedforward neural networks-Reference-Cited by-同舟云学术

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Short-term wave power forecasting with hybrid multivariate variational mode decomposition model integrated with cascaded feedforward neural networks

Published:2024-02 Issue: Volume:221 Page:119773
ISSN:0960-1481
Container-title:Renewable Energy
language:en
Short-container-title:Renewable Energy

Author:

Ali Mumtaz^ORCID,Prasad Ramendra,Jamei Mehdi,Malik Anurag^ORCID,Xiang Yong,Abdulla Shahab,Deo Ravinesh C.,Farooque Aitazaz A.,Labban Abdulhaleem H.^ORCID

Funder

Queensland Government

Department of Environment and Science, Queensland Government

Publisher

Elsevier BV

Subject

Renewable Energy, Sustainability and the Environment

Reference74 articles.

1. Renewable Energy Statistics 2022,2022

2. Assessment of wind and wave power characteristic and potential for hybrid exploration in Australia;Gao;Renew. Sustain. Energy Rev.,2022

3. Grid Codes for Renewable Powered Systems,2022

4. Artificial neural networks in the forecasting of wave parameters;Makarynskyy,2002

5. SWAN predictions of waves observed in shallow water onshore of complex bathymetry;Gorrell;Coast. Eng.,2011

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Short-Term Photovoltaic Power Generation Based on MVMD Feature Extraction and Informer Model;Applied Sciences;2024-07-18

2. Improving Wind Power Forecast Accuracy for Optimal Hybrid System Energy Management;Journal of Energy Resources Technology;2024-06-13

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