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Prediction of dynamic hysteresis loops of nano-crystalline cores

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dc.contributor.buuauthorHacıismailoğlu, Muhammed Cüneyt
dc.contributor.buuauthorKüçük, İlker Semih
dc.contributor.buuauthorDerebaşı, Naim
dc.contributor.departmentFen Edebiyat Fakültesi
dc.contributor.departmentFizik Ana Bilim Dalı
dc.contributor.orcid0000-0002-0781-3376
dc.contributor.orcid0000-0003-2546-0022
dc.contributor.researcheridK-7950-2012
dc.contributor.researcheridAAI-2254-2021
dc.contributor.scopusid8975743500
dc.contributor.scopusid6602910810
dc.contributor.scopusid11540936300
dc.date.accessioned2021-12-10T08:45:28Z
dc.date.available2021-12-10T08:45:28Z
dc.date.issued2009-03
dc.description.abstractDynamic hysteresis loops of a range of nano-crystalline cores have been obtained over a wide frequency range (1-50 kHz). A dynamic hysteresis model front measurements using an artificial neural network trained by the delta-bar-delta learning algorithm has been developed. The input parameters include the geometrical dimensions of cores, peak magnetic induction and magnetizing frequency. The results show the neural network model has an acceptable estimation capability for dynamic hysteresis loops of toroidal nano-crystalline cores.
dc.identifier.citationHacıismailoğlu, M. C. vd. (2009). "Prediction of dynamic hysteresis loops of nano-crystalline cores". Expert Systems with Applications, 36(2), Part 1, 2225-2227.
dc.identifier.endpage2227
dc.identifier.issn0957-4174
dc.identifier.issue2, Part 1
dc.identifier.scopus2-s2.0-56349165252
dc.identifier.startpage2225
dc.identifier.urihttps://doi.org/10.1016/j.eswa.2007.12.051
dc.identifier.urihttps://www.sciencedirect.com/science/article/pii/S0957417407006422
dc.identifier.urihttp://hdl.handle.net/11452/23167
dc.identifier.volume36
dc.identifier.wos000262178000122
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 modelling
dc.subjectNano-crystalline cores
dc.subjectNeural network
dc.subjectToroidal cores
dc.subjectComputer science
dc.subjectEngineering
dc.subjectOperations research & management science
dc.subjectCrystalline materials
dc.subjectHysteresis loops
dc.subjectMagnetic levitation vehicles
dc.subjectMagnetic materials
dc.subjectNeural networks
dc.subjectDelta-bar-delta
dc.subjectDynamic hysteresis loops
dc.subjectDynamic hysteresis modeling
dc.subjectDynamic hysteresis modelling
dc.subjectGeometrical dimensions
dc.subjectNanocrystalline cores
dc.subjectNeural network model
dc.subjectWide frequency range
dc.subjectHysteresis
dc.subject.scopusSilicon Steel; Soft Magnetic Materials; Induction Motors
dc.subject.wosComputer science, artificial intelligence
dc.subject.wosEngineering, electrical & electronic
dc.subject.wosOperations research & management science
dc.titlePrediction of dynamic hysteresis loops of nano-crystalline cores
dc.typeArticle
dc.wos.quartileQ1
dspace.entity.typePublication
local.contributor.departmentFen Edebiyat Fakültesi/Fizik Ana Bilim Dalı
local.indexed.atScopus
local.indexed.atWOS

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