Findings from Yangzhou University in the Area of Artificial Neural Networks Described (Comparative Study of Physical-based Constitutive Model and Bp Artificial Neural Network Model In Predicting High Temperature Flow Stress of Az80 Magnesium ...)

摘要

By a News Reporter-Staff News Editor at Network Daily News – Data detailed on Artificial Neural Networks have been presented. According to news reporting originating from Jiangsu, People’s Republic of China, by NewsRx correspondents, research stated, “Based on the hot compression test data of as-cast AZ80 magnesium alloy under the conditions of deformation temperature of 250 similar to 400 degrees C and strain rate of 0.001 similar to 1 s(-1), a physical-based constitutive model based on the stress dislocation correlation and dynamic recrystallization dynamics and an artificial neural network (ANN) model based on feedforward backpropagation algorithm were established to predict the thermal deformation behavior of AZ80 magnesium alloy. Three statistical indicators, correlation coefficient ?, mean absolute relative error (AARE), and relative error (RE), were used to verify the prediction accuracy of these two models.”