The Network Prediction of Hot Temperature Flow Stress and Dynamic Recrystallization of AZ61 Alloy
2014 ◽
Vol 989-994
◽
pp. 544-547
Keyword(s):
In this paper, the Back-Propagation neural network (BP network) and the establishment of the AZ61 magnesium alloy high temperature constitutive model and test data obtained for training the neural network, after training the neural network to become a knowledge-based constitutive model formed AZ61 magnesium alloy flow stress and dynamic recrystallization of the neural network model tested by the neural network model with traditional regression methods predict contrast, results showed that the higher the accuracy of the neural network model for dealing with a large number of test data to establish the constitutive relations of materials with high stress and promotion of value.
2019 ◽
Vol 2673
(4)
◽
pp. 108-116
◽
Keyword(s):
Keyword(s):
2019 ◽
Vol 24
(2)
◽
pp. 217-230