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Neural Computing and Applications

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01-09-2013 | Original Article

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

Authors: Gholamreza Khalaj, Mahdi Khoeini, Meysam Khakian-Qomi

Published in: Neural Computing and Applications | Issue 3-4/2013

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Abstract

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.

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Title: ANN-based prediction of ferrite fraction in continuous cooling of microalloyed steels
Authors: Gholamreza Khalaj
Mahdi Khoeini
Meysam Khakian-Qomi
Publication date: 01-09-2013
Publisher: Springer London
Published in: Neural Computing and Applications / Issue 3-4/2013
Print ISSN: 0941-0643
Electronic ISSN: 1433-3058
DOI: https://doi.org/10.1007/s00521-012-0992-4

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