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

Please use this identifier to cite or link to this item: http://hdl.handle.net/11452/33135

Title:	Prediction of giant magneto-impedance effect in amorphous glass-coated micro-wires using artificial neural network
Authors:	Uludağ Üniversitesi/Fen-Edebiyat Fakültesi/Fizik Anabilim Dalı. 0000-0002-4467-3456 Kaya, Aslı Ayten W-1759-2017 55779992300
Keywords:	Mathematics Giant magneto-impedance effect Amorphous micro-wires Modeling Artificial neural network Magnetoimpedance Sensors
Issue Date:	Apr-2013
Publisher:	Springer
Citation:	Kaya, 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.
Abstract:	This 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.
URI:	https://doi.org/10.1186/1029-242X-2013-216 http://hdl.handle.net/11452/33135
ISSN:	1029-242X https://journalofinequalitiesandapplications.springeropen.com/articles/10.1186/1029-242X-2013-216
Appears in Collections:	Scopus Web of Science

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