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Application of Genetic Algorithms to the Implementation of Fractional Electromagnetic Potentials

dc.contributor.authorJesus, Isabel S.
dc.contributor.authorTenreiro Machado, J. A.
dc.contributor.authorCunha, J. Boaventura
dc.date.accessioned2019-04-02T11:07:58Z
dc.date.available2019-04-02T11:07:58Z
dc.date.issued2006-09
dc.description.abstractA genetic algorithm (GA) is a search technique based on the natural selection process. The GAs provide further flexibility and robustness that are unique for signal process. Recently, a closer look of some phenomena present in electrical systems, such as motors, transformers and lines, and the motivation towards the development of comprehensive models, seem to point out the requirement for a fractional calculus approach. Bearing these ideas in mind, we address the analysis and the synthesis of fractional-order multipoles, based in a GA optimization scheme.pt_PT
dc.description.versionN/Apt_PT
dc.identifier.urihttp://hdl.handle.net/10400.22/13326
dc.language.isoengpt_PT
dc.subjectElectrical potentialpt_PT
dc.subjectFractional order systemspt_PT
dc.subjectGenetic algorithmpt_PT
dc.titleApplication of Genetic Algorithms to the Implementation of Fractional Electromagnetic Potentialspt_PT
dc.typeconference object
dspace.entity.typePublication
oaire.citation.conferencePlaceStirlingshire, Scotlandpt_PT
oaire.citation.endPage12pt_PT
oaire.citation.startPage1pt_PT
oaire.citation.titleFifth International Conference on Engineering Computational Technologypt_PT
person.familyNameJesus
person.familyNameTenreiro Machado
person.givenNameIsabel S.
person.givenNameJ. A.
person.identifier.ciencia-id131A-D722-8D60
person.identifier.ciencia-id7A18-4935-5B29
person.identifier.orcid0000-0002-7545-5822
person.identifier.orcid0000-0003-4274-4879
person.identifier.ridM-2173-2013
person.identifier.scopus-author-id9333348500
person.identifier.scopus-author-id55989030100
rcaap.rightsopenAccesspt_PT
rcaap.typeconferenceObjectpt_PT
relation.isAuthorOfPublicatione7f8ed34-e3e4-49f5-815b-861c7f28936e
relation.isAuthorOfPublication82cd5c17-07b6-492b-b3e3-ecebdad1254f
relation.isAuthorOfPublication.latestForDiscovery82cd5c17-07b6-492b-b3e3-ecebdad1254f

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