Prediction of flow stresses at high temperatures with artificial neural networks

On the basis of the data obtained on Gleeble 1500 Thermal Simulator, the predicting models for the relation between stable flow stress during high temperature plastic deformation and deformation strain, strain rate and temperature for 1420 Al Li alloy have been developed with BP artificial neural networks method. The results show that the model on basis of BPNN is practical and it reflects the actual feature of the deforming process. It states that the difference between the actual value and the output of the model is in order of 5%. [

On the basis of the data obtained on Gleeble-1500 Thermal Simulator, the predicting models for the relation between stable flow stress during high temperature plastic deformation and deformation strain, strain rate and temperature for 1420 AI-Li alloy have been developed with BP artificial neural networks method. The results show that the model on basis of BPNN is practical and it reflects the actual feature of the deforming process. It states that the difference between the actual value and the output of the model is in order of 5%.