中文摘要：

以便预言并且控制 Cu-Cr-Sn-Zn 合金的性质，经由一个人工的神经网络(ANN ) 的老化进程的一个模型印射在老化过程和坚硬和 Cu-Cr-Sn-Zn 合金的电的传导性性质的参数之间的非线性的关系的方法被安装。结果证明 ANN 模型是为性质分析和老化 Cu-Cr-Sn-Zn 合金的预言的一个很有用、精确的工具。在 470510 点年老

英文摘要：

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.