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In order to predict and control the properties of Cu-Cr-Sn-Zn alloy,a model of aging processes via an artificial neural network(ANN) method to map the non-linear relationship between parameters of aging process and the hardness and electrical conductivity properties of the Cu-Cr-Sn-Zn alloy was set up.The results show that the ANN model is a very useful and accurate tool for the property analysis and prediction of aging Cu-Cr-Sn-Zn alloy.Aged at 470-510 ℃ for 4-1 h,the optimal combinations of hardness 110-117(HV) and electrical conductivity 40.6-37.7 S/m are available respectively.
In order to predict and control the properties of Cu-Cr-Sn-Zn alloy, a model of aging processes via an artificial neural network (ANN) method to map the non-linear relationship between parameters of aging process and the hardness and electrical conductivity properties of the Cu-Cr-Sn-Zn alloy was set up. The results show that the ANN model is a very useful and accurate tool for the property analysis and prediction of aging Cu-Cr-Sn-Zn alloy. Aged at 470- 510 ° C for 4-1 h, the optimal combinations of hardness 110-117 (HV) and electrical conductivity 40.6-37.7 S / m are available respectively.