Establishing the knowledge repository of rapidly solidified aging Cu-Cr-Zr alloy on the artificial neural-network

The non-linear relationship between parameters of rapidly solidified aging processes and mechanical and electrical properties of Cu-Cr-Zr alloy is available by using a supervised artificial neural network (ANN). A knowledge repository of rapidly solidified aging processes is established via sufficient data learning by the network. The predicted values of the neural network are in accordance with the tested data. So an effective measure for foreseeing and controlling the properties of the processing is provided.