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J-A hysteresis model parameters estimation using GA

dc.contributor.authorZidarič, Bogomir
dc.contributor.authorMiljavec, Damijan
dc.date.accessioned2011-01-21T06:46:14Z
dc.date.available2011-01-21T06:46:14Z
dc.date.issued2005
dc.identifier.citationAdvances in electrical and electronic engineering. 2005, vol. 4, no. 3, p. 174-177.en
dc.identifier.issn1336-1376
dc.identifier.urihttp://hdl.handle.net/10084/83690
dc.description.abstractThis paper presents the Jiles and Atherton (J-A) hysteresis model parameter estimation for soft magnetic composite (SMC) material. The calculation of Jiles and Atherton hysteresis model parameters is based on experimental data and genetic algorithms (GA). Genetic algorithms operate in a given area of possible solutions. Finding the best solution of a problem in wide area of possible solutions is uncertain. A new approach in use of genetic algorithms is proposed to overcome this uncertainty. The basis of this approach is in genetic algorithm built in another genetic algorithm.en
dc.format.extent107271 bytescs
dc.format.mimetypeapplication/pdfcs
dc.language.isoenen
dc.publisherŽilinská univerzita v Žiline. Elektrotechnická fakultaen
dc.relation.ispartofseriesAdvances in electrical and electronic engineeringen
dc.relation.urihttp://advances.utc.sk/index.php/AEEEen
dc.rightsCreative Commons Attribution 3.0 Unported (CC BY 3.0)en
dc.rights© Žilinská univerzita v Žiline. Elektrotechnická fakultaen
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/en
dc.titleJ-A hysteresis model parameters estimation using GAen
dc.typearticleen
dc.rights.accessopenAccess
dc.type.versionpublishedVersioncs
dc.type.statusPeer-reviewedcs


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  • AEEE. 2005, vol. 4 [32]
  • OpenAIRE [5085]
    Kolekce určená pro sklízení infrastrukturou OpenAIRE; obsahuje otevřeně přístupné publikace, případně další publikace, které jsou výsledkem projektů rámcových programů Evropské komise (7. RP, H2020, Horizon Europe).

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Creative Commons Attribution 3.0 Unported (CC BY 3.0)
Except where otherwise noted, this item's license is described as Creative Commons Attribution 3.0 Unported (CC BY 3.0)