The non-linear relationship between parameters of rapidly solidified aging processes and mechancal andelectrical properties of Cu-Cr-Zr alloy is avaitable by using a supervised artificial neural network (ANN). A knowledgerepository of rapidly solidified aging processes is established via sufficient data learning by the network. The predictedvalues of the neural network are in accordance with the tested data. So an effective measare for foreseeing and controllingthe properties of the processing is provided. The non-linear relationship between parameters of rapidly solidified aging processes and mechancal andelectrical properties of Cu-Cr-Zr alloy is avaitable by using a supervised artificial neural network (ANN). A knowledgerepository 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 measare for foreseeing and controlling the properties of the processing is provided.