The rapidly solidified aging copper alloy by BP neural network

Abstract

Rapid solidifiation is a kind of new process for enhancing the hardness and electrical conductivity of Cu−Cr−Zr copper alloy. The use of BP neural network (NN) is presented to model the non-linear relationship between parameters of age hardening processes and the mechanical and electrical properties of rapdily solidified Cu−Cr−Zr alloy. The improved model is developed by the Levenberg-Marquardt training algorithm and the good generalization performance is demonstrated. So, an important foundation has been laid for optimisticaly controlling the rapidly solidified aging processes of Cu−Cr−Zr alloy.

Keywords

Cu−Cr−Zr alloy / rapid solidification / aging / BP neural network / Levenberg-Marquard algorithm

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