Based on BP neural network technology

the parameters of extrusion speed

extrusion passes and extrusion method were designed for the input layer

and the tensile strength was designed as the output layer parameter

thus BP neural network model was established for analyzing effects of ECAP strong deformation on properties of Cu-3Cr alloy.Meanwhile

experimental verification of metallurgical microstructure ovservation and SEM was carried out.The results show that the relative error between the predicted and experimental values of the tensile strength between BP neural network outputs and experimental value is less than 2% with the average prediction error of 1.4%

showing a higher prediction accuracy of the model.From the view of improving tensile strength of the alloy

the optimized ECAP process parameters for Cu-3Cr alloy were presented as follows:extrusion speed of 5mm/s

the extrusion pass of 4

and the extrusion method with rotating 180°and then entering the next pass after one squeeze.