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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.orcid0000-0002-4467-3456tr_TR
dc.contributor.researcheridW-1759-2017tr_TR
dc.contributor.scopusid55779992300tr_TR
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.en_US
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.en_US
dc.identifier.issn1029-242X
dc.identifier.issnhttps://journalofinequalitiesandapplications.springeropen.com/articles/10.1186/1029-242X-2013-216
dc.identifier.scopus2-s2.0-84894620389tr_TR
dc.identifier.urihttps://doi.org/10.1186/1029-242X-2013-216
dc.identifier.urihttp://hdl.handle.net/11452/33135
dc.identifier.volume2013tr_TR
dc.identifier.wos000318843400001
dc.indexed.wosSCIEen_US
dc.language.isoenen_US
dc.publisherSpringeren_US
dc.relation.journalJournal of Inequalities and Applicationsen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergitr_TR
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectMathematicsen_US
dc.subjectGiant magneto-impedance effecten_US
dc.subjectAmorphous micro-wiresen_US
dc.subjectModelingen_US
dc.subjectArtificial neural networken_US
dc.subjectMagnetoimpedanceen_US
dc.subjectSensorsen_US
dc.subject.scopusMagnetic Sensors; Electric Impedance; Ribbonsen_US
dc.subject.wosMathematics, applieden_US
dc.subject.wosMathematicsen_US
dc.titlePrediction of giant magneto-impedance effect in amorphous glass-coated micro-wires using artificial neural networken_US
dc.typeArticle
dc.wos.quartileQ2en_US
dspace.entity.typePublication
local.contributor.departmentFen Edebiyat Fakültesi/Fizik Ana Bilim Dalıtr_TR
local.indexed.atScopus
local.indexed.atWOS

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