Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/81196
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dc.contributorDepartment of Civil and Environmental Engineering-
dc.creatorDineva, A-
dc.creatorMosavi, A-
dc.creatorArdabili, S-
dc.creatorVajda, I-
dc.creatorShamshirband, S-
dc.creatorRabczuk, T-
dc.creatorChau, KW-
dc.date.accessioned2019-08-23T08:29:42Z-
dc.date.available2019-08-23T08:29:42Z-
dc.identifier.urihttp://hdl.handle.net/10397/81196-
dc.language.isoenen_US
dc.publisherMolecular Diversity Preservation International (MDPI)en_US
dc.rights© 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).en_US
dc.rightsThe following publication Dineva A, Mosavi A, Faizollahzadeh Ardabili S, Vajda I, Shamshirband S, Rabczuk T, Chau K-W. Review of Soft Computing Models in Design and Control of Rotating Electrical Machines. Energies. 2019; 12(6):1049 is available at https://doi.org/10.3390/en12061049en_US
dc.subjectArtificial intelligenceen_US
dc.subjectBig dataen_US
dc.subjectComputational intelligenceen_US
dc.subjectControlen_US
dc.subjectData scienceen_US
dc.subjectDeep learningen_US
dc.subjectElectric motor drivesen_US
dc.subjectElectric vehiclesen_US
dc.subjectElectrical engineeringen_US
dc.subjectEnergy informaticsen_US
dc.subjectEnergy managementen_US
dc.subjectEnergy systemsen_US
dc.subjectEnsemble modelsen_US
dc.subjectHybrid modelsen_US
dc.subjectMachine learningen_US
dc.subjectRotating electrical machinesen_US
dc.subjectSoft computingen_US
dc.titleReview of soft computing models in design and control of rotating electrical machinesen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.volume12-
dc.identifier.issue6-
dc.identifier.doi10.3390/en12061049-
dcterms.abstractRotating electrical machines are electromechanical energy converters with a fundamental impact on the production and conversion of energy. Novelty and advancement in the control and high-performance design of these machines are of interest in energy management. Soft computing methods are known as the essential tools that significantly improve the performance of rotating electrical machines in both aspects of control and design. From this perspective, a wide range of energy conversion systems such as generators, high-performance electric engines, and electric vehicles, are highly reliant on the advancement of soft computing techniques used in rotating electrical machines. This article presents the-state-of-the-art of soft computing techniques and their applications, which have greatly influenced the progression of this significant realm of energy. Through a novel taxonomy of systems and applications, the most critical advancements in the field are reviewed for providing an insight into the future of control and design of rotating electrical machines.-
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationEnergies, 2019, v. 12, no. 6, 1049-
dcterms.isPartOfEnergies-
dcterms.issued2019-
dc.identifier.scopus2-s2.0-85065339282-
dc.identifier.eissn1996-1073-
dc.identifier.artn1049-
dc.description.validate201908 bcma-
dc.description.oaVersion of Recorden_US
dc.identifier.FolderNumberOA_Scopus/WOSen_US
dc.description.pubStatusPublisheden_US
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