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Prediction of giant magneto-impedance effect in amorphous glass-coated micro-wires using artificial neural network

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dc.contributor.buuauthorKaya, Aslı Ayten
dc.contributor.departmentFen Edebiyat Fakültesi
dc.contributor.departmentFizik Ana Bilim Dalı
dc.contributor.orcid0000-0002-4467-3456
dc.contributor.researcheridW-1759-2017
dc.contributor.scopusid55779992300
dc.date.accessioned2023-06-23T07:35:02Z
dc.date.available2023-06-23T07:35:02Z
dc.date.issued2013-04
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.
dc.identifier.citationKaya, A. A. (2013). “Prediction of giant magneto-impedance effect in amorphous glass-coated micro-wires using artificial neural network”. Journal of inequalities and applications, 2013.
dc.identifier.issn1029-242X
dc.identifier.issnhttps://journalofinequalitiesandapplications.springeropen.com/articles/10.1186/1029-242X-2013-216
dc.identifier.scopus2-s2.0-84894620389
dc.identifier.urihttps://doi.org/10.1186/1029-242X-2013-216
dc.identifier.urihttp://hdl.handle.net/11452/33135
dc.identifier.volume2013
dc.identifier.wos000318843400001
dc.indexed.wosSCIE
dc.language.isoen
dc.publisherSpringer
dc.relation.journalJournal of Inequalities and Applications
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subjectMathematics
dc.subjectGiant magneto-impedance effect
dc.subjectAmorphous micro-wires
dc.subjectModeling
dc.subjectArtificial neural network
dc.subjectMagnetoimpedance
dc.subjectSensors
dc.subject.scopusMagnetic Sensors; Electric Impedance; Ribbons
dc.subject.wosMathematics, applied
dc.subject.wosMathematics
dc.titlePrediction of giant magneto-impedance effect in amorphous glass-coated micro-wires using artificial neural network
dc.typeArticle
dc.wos.quartileQ2
dspace.entity.typePublication
local.contributor.departmentFen Edebiyat Fakültesi/Fizik Ana Bilim Dalı
local.indexed.atScopus
local.indexed.atWOS

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