Artificial neural network to predict the effect of heat treatments on Vickers microhardness of low-carbon Nb microalloyed steels

@article{Khalaj2011ArtificialNN,
  title={Artificial neural network to predict the effect of heat treatments on Vickers microhardness of low-carbon Nb microalloyed steels},
  author={Gholamreza Khalaj and Hossein Yoozbashizadeh and Alireza Khodabandeh and Ali Nazari},
  journal={Neural Computing and Applications},
  year={2011},
  volume={22},
  pages={879-888}
}
In the present study, an artificial neural networks-based model (ANNs) was developed to predict the Vickers microhardness of low-carbon Nb microalloyed steels. Fourteen parameters affecting the Vickers microhardness were considered as inputs, including the austenitizing temperature, cooling rate, initial austenite grain size, different chemical compositions and Nb in solution. The network was then trained to predict the Vickers microhardness amounts as outputs. A Multilayer feed-forward back… CONTINUE READING