Artificial neural network modeling of flow stress in hot rolling


Autoria(s): Aghasafari,P; Abdi,H; Salimi,M
Data(s)

01/01/2014

Resumo

In this study, an artificial neural network model is proposed to predict the flow stress variations during the hot rolling process. Optimization of the proposed neural network with respect to number of neurons within the hidden layer, different training methods and transfer functions of the neural network is performed. The results of the optimal network were compared with those of the conventional analytic method and it is shown that using an optimal neural network the mean calculated error is drastically reduced.

Identificador

http://hdl.handle.net/10536/DRO/DU:30071850

Idioma(s)

eng

Publicador

Iron and Steel Institute of Japan

Relação

http://dro.deakin.edu.au/eserv/DU:30071850/abdi-artificialneural-2014.pdf

http://www.dx.doi.org/10.2355/isijinternational.54.872

Direitos

2014, Iron and Steel Institute of Japan

Palavras-Chave #Artificial neural network #Flow stress #Hot rolling #Modeling #Optimization #Science & Technology #Technology #Metallurgy & Metallurgical Engineering #PREDICTION
Tipo

Journal Article