The author collected 252 continuous cooling transformation (CCT) diagrams of steels and developed artificial neural network(ANN) models to predict the critical cooling velocities of bainite start transformation(CCVBST) of steels. The comparison of the predicted values with the measured ones showed that the prediction accuracy of different ANN models is different. Effects of alloying elements such as silicon and boron on the CCVBST were analysed quantitatively using ANN model with highest accuracy, most of the computation results accord well with the measured ones.
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