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

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Kaya, Aslı Ayten

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Springer

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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.

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Mathematics, Giant magneto-impedance effect, Amorphous micro-wires, Modeling, Artificial neural network, Magnetoimpedance, Sensors

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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.

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