Based on the experimental data of superplastic tensile tests

the neural network prediction model of flow stress of WSTi3515 Sburn-resistant titanium alloy during superplastic deformation was established using BP artificial neural network.The inputs of the model include deformation temperature

strain and strain rate

while the output of the model is the flow stress.The structure adopted four layers back propagation neural network model with 3×10×12×1 double hidden layers.The results show that the BP neural network model can well describe the highly nonlinear complex relationship among the thermodynamic parameters of WSTi3515 Salloy during superplastic deformation.It also can accurately predict the flow stress during superplastic tensile tests

and the average relative error is 1.08%.