Publication:
Modelling of power loss in electrical steels

dc.contributor.buuauthorKüçük, İ.
dc.contributor.buuauthorErtürk, K.
dc.contributor.buuauthorHaciismailoğlu, M. C.
dc.contributor.buuauthorHACIİSMAİLOĞLU, MUHAMMED CÜNEYT
dc.contributor.buuauthorDerebaşı, Naim
dc.contributor.buuauthorDEREBAŞI, NAİM
dc.contributor.departmentBursa Uludağ Üniversitesi/Fen Edebiyat Fakültesi/Fizik Bölümü.
dc.contributor.orcid0000-0002-0781-3376
dc.contributor.orcid0000-0003-2546-0022
dc.contributor.researcheridABA-5148-2020
dc.contributor.researcheridAAI-2254-2021
dc.contributor.researcheridK-7950-2012
dc.date.accessioned2024-10-10T05:31:00Z
dc.date.available2024-10-10T05:31:00Z
dc.date.issued2008-01-01
dc.descriptionBu çalışma, 09-12 Temmuz 2007 tarihleri arasında Kosice[Slovakya]’da düzenlenen 13t. Czech and Slovak Conference on Magnetism (CSMAG'07)’da bildiri olarak sunulmuştur.
dc.description.abstractThis paper presents a new artificial neural network approach based on loss separation model to compute power loss on different types of electrical steels. The network was trained by a Levenberg-Marquardt algorithm. The results obtained by using the proposed model were compared with a commonly used conventional model. The comparison has shown that the neural network model is in good agreement with experimental data with respect to the conventional model.
dc.identifier.endpage150
dc.identifier.issn0587-4246
dc.identifier.issue1
dc.identifier.startpage147
dc.identifier.urihttps://hdl.handle.net/11452/46159
dc.identifier.volume113
dc.identifier.wos000253324800037
dc.indexed.wosWOS.ISTP
dc.indexed.wosWOS.SCI
dc.language.isoen
dc.publisherPolish Acad Sciences Inst Physics
dc.relation.journalActa Physica Polonica A
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectToroidal cores
dc.subjectScience & technology
dc.subjectPhysical sciences
dc.subjectPhysics, multidisciplinary
dc.subjectPhysics
dc.titleModelling of power loss in electrical steels
dc.typeArticle
dc.typeProceedings Paper
dspace.entity.typePublication
relation.isAuthorOfPublication82584aef-f502-4b13-a805-f9de1bf37ec0
relation.isAuthorOfPublication0c85f61f-70fa-4f0d-83a0-a3a0ac50e069
relation.isAuthorOfPublication.latestForDiscovery82584aef-f502-4b13-a805-f9de1bf37ec0

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