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Artificial neural network modeling of flow stress in hot rolling

Aghasafari,P, Abdi,H and Salimi,M 2014, Artificial neural network modeling of flow stress in hot rolling, ISIJ international, vol. 54, no. 4, pp. 872-879, doi: 10.2355/isijinternational.54.872.

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Title Artificial neural network modeling of flow stress in hot rolling
Author(s) Aghasafari,P
Abdi,HORCID iD for Abdi,H orcid.org/0000-0001-6597-7136
Salimi,M
Journal name ISIJ international
Volume number 54
Issue number 4
Start page 872
End page 879
Publisher Iron and Steel Institute of Japan
Place of publication Tokyo, Japan
Publication date 2014
ISSN 0915-1559
Keyword(s) Artificial neural network
Flow stress
Hot rolling
Modeling
Optimization
Science & Technology
Technology
Metallurgy & Metallurgical Engineering
PREDICTION
Summary 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.
Language eng
DOI 10.2355/isijinternational.54.872
Field of Research 080108 Neural, Evolutionary and Fuzzy Computation
Socio Economic Objective 970109 Expanding Knowledge in Engineering
HERDC Research category C1 Refereed article in a scholarly journal
ERA Research output type C Journal article
Copyright notice ©2014, Iron and Steel Institute of Japan
Free to Read? Yes
Persistent URL http://hdl.handle.net/10536/DRO/DU:30071850

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Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.