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Prediction of giant magneto-impedance effect in amorphous glass-coated micro-wires using artificial neural network Proceedings of the International Congress in Honour of Professor Hari M. Srivastava

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dc.contributor.authorKaya, Asli Ayten
dc.contributor.buuauthorKaya, Asli Ayten
dc.contributor.departmentFen Edebiyat Fakültesi
dc.contributor.departmentFizik Bölümü
dc.contributor.scopusid55779992300
dc.date.accessioned2025-05-13T10:12:32Z
dc.date.issued2013-07-08
dc.description.abstractThis paper deals with a prediction of a giant magneto-impedance (GMI) effect on amorphous micro-wires using an artificial neural network (ANN). The prediction model has three hidden layers with fifteen neurons and full connectivity between them. The ANN model is used to predict the GMI effect for Co70.3Fe3.7B10Si13Cr3 glass-coated micro-wire. The results show that the ANN model has a 98.99% correlation with experimental data. © 2013 Kaya; licensee Springer.
dc.identifier.doi10.1186/1029-242X-2013-216
dc.identifier.issn1025-5834
dc.identifier.scopus2-s2.0-84879629858
dc.identifier.urihttps://hdl.handle.net/11452/52516
dc.identifier.urihttps://link.springer.com/content/pdf/10.1186/1029-242X-2013-216.pdf
dc.identifier.volume2013
dc.indexed.scopusScopus
dc.language.isoen
dc.relation.journalJournal of Inequalities and Applications
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subjectModeling
dc.subjectGiant magneto-impedance effect
dc.subjectArtificial neural network
dc.subjectAmorphous micro-wires
dc.subject.scopusAmorphous Material; Magnetic Field; Anisotropy
dc.titlePrediction of giant magneto-impedance effect in amorphous glass-coated micro-wires using artificial neural network Proceedings of the International Congress in Honour of Professor Hari M. Srivastava
dc.typeArticle
dspace.entity.typePublication
local.contributor.departmentFen Edebiyat Fakültesi/Fizik Bölümü

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