Repository logo
 

Artificial Intelligence-Driven Advanced Wave Energy Planning and Control: Framework, Challenges and Perspectives [Editorial]

Simple item page
aut.relation.endpage10
aut.relation.issue0
aut.relation.startpage1
aut.relation.volume0
dc.contributor.authorYang, Bo
dc.contributor.authorZhou, Guo
dc.contributor.authorZhou, Shuai
dc.contributor.authorRen, Yaxing
dc.date.accessioned2025-08-27T00:07:16Z
dc.date.available2025-08-27T00:07:16Z
dc.date.issued2025-08-22
dc.descriptionWith the continuous increase in global population, the demand for energy is upgrading at an unprecedented rate. At present, fossil fuels dominate the global energy landscape, but their limitations lay the groundwork for the upcoming global energy crisis. The non renewable nature of fossil fuels, coupled with increasing energy consumption, poses a significant threat to the long-term energy security of the world. In addition, the combustion of fossil fuels releases a large amount of air pollutants such as carbon dioxide and sulfur dioxide, leading to serious environmental pollution and climate change. These environmental issues have far-reaching impacts, including rising sea levels, extreme weather events, and loss of biodiversity.
dc.identifier.doi10.32604/ee.2025.069600
dc.identifier.issn1546-0118
dc.identifier.urihttp://hdl.handle.net/10292/19725
dc.languageen
dc.publisherTech Science Press
dc.relation.urihttps://www.techscience.com/energy/online/detail/24080
dc.rightsCopyright © 2025 The Authors. Published by Tech Science Press. This work is licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
dc.rights.accessrightsOpenAccess
dc.subject0914 Resources Engineering and Extractive Metallurgy
dc.subjectEnergy
dc.subjectArtificial intelligence
dc.subjectwave energy
dc.subjectWEC control
dc.subjecthybrid planning
dc.titleArtificial Intelligence-Driven Advanced Wave Energy Planning and Control: Framework, Challenges and Perspectives [Editorial]
dc.typeJournal Article
pubs.elements-id625496

Files

Original bundle

Now showing 1 - 1 of 1
Thumbnail Image
Name:
Yang et al_2025_Editorial_ AI driven advanced wave energy.pdf
Size:
527.52 KB
Format:
Adobe Portable Document Format
Description:
Journal article
Download

Collections

School of Engineering, Computer and Mathematical Sciences - Te Kura Mātai Pūhanga, Rorohiko, Pāngarau