Employment of the artificial neural networks for prediction of magnetic properties of the metallic amorphous alloys

What is it about?

The aim of the work is to employ the artificial neural networks for prediction of magnetic saturation of the amorphous alloys with the iron and cobalt matrix. It has been assumed that the artificial neural networks can be used to assign the relationship between the chemical compositions of amorphous alloys, temperature of heat treatment and magnetic saturation. In order to determine the relationship it has been necessary to work out a suitable calculation model. It has been proved that employment of genetic algorithm to selection of input neurons can be very useful tool to improve artificial neural network calculation results. The attempt to use the artificial neural networks for predicting the effect of the chemical composition and temperature of heat treatment on the magnetic saturation BS succeeded, as the level of the obtained results was acceptable.

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Why is it important?

The results of research make it possible to calculate with a certain admissible error the magnetic saturation Bs value basing on combinations of concentrations of the particular elements and heat treatment temperature. In this paper it has been presented an original trial of prediction of the required magnetic properties of the iron and cobalt amorphous alloys.