Use of Neutral-Network Approximation for Prediction of the Microhardness of Nanocomposite Coatings

Abstract

Results of experimental investigations into the microhardness of metal–ceramic nanocomposite coatings have been approximated with the apparatus of artificial neural networks. A neutral-network dependence of the microhardness on the concentration of the metal phase and microhardnesses of “pure” phases has been obtained. An algorithm of employment of a neural network for calculation of the microhardness of nanocomposites has been presented.