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dc.contributor.authorHatti, Mustapha
dc.contributor.authorDenai, Mouloud
dc.date.accessioned2020-10-15T00:10:12Z
dc.date.available2020-10-15T00:10:12Z
dc.date.issued2020-08-20
dc.identifier.citationHatti , M & Denai , M 2020 , ' Introduction to the Special Section on Artificial Intelligence in Renewable Energetic Systems ' , Computers and Electrical Engineering . < https://www.sciencedirect.com/journal/computers-and-electrical-engineering/special-issue/10BDMNFW2XS >
dc.identifier.issn0045-7906
dc.identifier.otherPURE: 22798353
dc.identifier.otherPURE UUID: a9940eaa-fc8e-4b78-bf5e-f85aab1f70be
dc.identifier.urihttp://hdl.handle.net/2299/23266
dc.description.abstractThe world’s today is in an unprecedented and urgent need to optimize energy consumption and accelerate the transition towards green, low-carbon electricity generation. To face the various challenges in the digital transformation of the energy ecosystem, technologies such as Big Data Analytics, Machine Learning and Artificial Intelligence (AI) are poised to play an increasingly important role in the years ahead. Expanding the adoption of AI technology across the energy sector will enable better control and management of energy consumption, anticipating network malfunctions, or even optimizing infrastructure assets. The aim of this special section is to disseminate the latest and ongoing research and technological advancements on the application of AI in modeling, control and optimization of Renewable and Alternative Energy Systems and future smart electricity networks.en
dc.language.isoeng
dc.relation.ispartofComputers and Electrical Engineering
dc.titleIntroduction to the Special Section on Artificial Intelligence in Renewable Energetic Systemsen
dc.contributor.institutionCentre for Engineering Research
dc.contributor.institutionCommunications and Intelligent Systems
dc.contributor.institutionSchool of Physics, Engineering & Computer Science
dc.contributor.institutionDepartment of Engineering and Technology
dc.description.statusPeer reviewed
dc.date.embargoedUntil2021-08-20
dc.identifier.urlhttps://www.sciencedirect.com/journal/computers-and-electrical-engineering/special-issue/10BDMNFW2XS
rioxxterms.versionAM
rioxxterms.typeJournal Article/Review
herts.preservation.rarelyaccessedtrue


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