ANN-based prediction of ferrite fraction in continuous cooling of microalloyed steels

作者：Khalaj Gholamreza^*; Khoeini Mahdi; Khakian Qomi Meysam

来源：Neural Computing & Applications, 2013, 23(3-4): 769-777.

DOI：10.1007/s00521-012-0992-4

• Artificial neural network (ANN)
• Microalloyed steel
• Continuous cooling
• Low-carbon Nb steel

In the present study, an artificial neural networks-based model was developed to predict the ferrite fraction of microalloyed steels during continuous cooling. Fourteen parameters affecting the ferrite fraction were considered as inputs, including the cooling rate, initial austenite grain size, and different chemical compositions. The network was then trained to predict the ferrite fraction amounts as outputs. A multilayer feed-forward back-propagation network was developed and trained using experimental data form literatures. The predicted values are in very good agreement with the measured ones indicating that the developed model is very accurate and has the great ability for predicting the ferrite fraction.

• 出版日期2013-9