Publication:
Dynamic hysteresis modelling for nano-crystalline cores

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dc.contributor.buuauthorKüçük, İlker Semih
dc.contributor.buuauthorHacıismailoğlu, Muhammed Cüneyt
dc.contributor.buuauthorDerebaşı, Naim
dc.contributor.departmentFen Edebiyat Fakültesi
dc.contributor.departmentFizik Bölümü
dc.contributor.orcid0000-0002-0781-3376
dc.contributor.orcid0000-0003-2546-0022
dc.contributor.researcheridK-7950-2012
dc.contributor.researcheridAAI-2254-2021
dc.contributor.scopusid6602910810
dc.contributor.scopusid8975743500
dc.contributor.scopusid11540936300
dc.date.accessioned2022-03-18T08:42:04Z
dc.date.available2022-03-18T08:42:04Z
dc.date.issued2009-03
dc.description.abstractThis paper presents all artificial neural network approach based oil dynamic Preisach model to compute hysteresis loops of nano-crystalline cores. The network has been trained by a Levenberg-Marquardt learning algorithm. The model is fast and does not require tremendous computational efforts. The results obtained by using the proposed model are in good agreement with experimental results.
dc.identifier.citationKüçük, İ. S. vd. (2009). "Dynamic hysteresis modelling for nano-crystalline cores". Expert Systems with Applications, 36(2), 3188-3190.
dc.identifier.endpage3190
dc.identifier.issn0957-4174
dc.identifier.issue2
dc.identifier.scopus2-s2.0-56349090867
dc.identifier.startpage3188
dc.identifier.urihttps://doi.org/10.1016/j.eswa.2008.01.084
dc.identifier.urihttps://www.sciencedirect.com/science/article/pii/S0957417408000997
dc.identifier.urihttp://hdl.handle.net/11452/25185
dc.identifier.volume36
dc.identifier.wos000262178100060
dc.indexed.wosSCIE
dc.language.isoen
dc.publisherPergamon-Elsevier Science
dc.relation.bap2002/4
dc.relation.journalExpert Systems with Applications
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectDynamic hysteresis model
dc.subjectNano-crystal
dc.subjectNeural network
dc.subjectNeural-network
dc.subjectGenetic algorithm
dc.subjectToroidal cores
dc.subjectPower losses
dc.subjectPrediction
dc.subjectComputer science
dc.subjectEngineering
dc.subjectOperations research & management science
dc.subjectCrystalline materials
dc.subjectHysteresis loops
dc.subjectNeural networks
dc.subjectArtificial neural network approach
dc.subjectComputational effort
dc.subjectDynamic hysteresis modeling
dc.subjectDynamic hysteresis modelling
dc.subjectLevenberg-Marquardt learning algorithms
dc.subjectNanocrystalline cores
dc.subjectON dynamics
dc.subjectHysteresis
dc.subject.scopusSilicon Steel; Soft Magnetic Materials; Iron
dc.subject.wosComputer science, artificial intelligence
dc.subject.wosEngineering, electrical & electronic
dc.subject.wosOperations research & management science
dc.titleDynamic hysteresis modelling for nano-crystalline cores
dc.typeArticle
dc.wos.quartileQ1
dspace.entity.typePublication
local.contributor.departmentFen Edebiyat Fakültesi/Fizik Bölümü
local.indexed.atScopus
local.indexed.atWOS

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