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Modelling of elastic modulus degradation in sheet metal forming using back propagation neural network

The aim of this study is to develop an elastic modulus predictive model during unloading of plastically prestrained SPCC sheet steel. The model was developed using the back propagation neural networks (BPNN) based on the experimental tension unloading data. The method involves selecting the archit...

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Main Authors: M. R. Jamli,, A. K. Ariffin,, Dzuraidah Abd. Wahab,
Format: Article
Language:English
Published: Fakulti Kejuruteraan ,UKM,Bangi. 2015
Online Access:http://journalarticle.ukm.my/9504/1/4.pdf
http://journalarticle.ukm.my/9504/
http://www.ukm.my/jkukm/?page_id=557
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spelling my-ukm.journal.95042016-12-14T06:50:08Z http://journalarticle.ukm.my/9504/ Modelling of elastic modulus degradation in sheet metal forming using back propagation neural network M. R. Jamli, A. K. Ariffin, Dzuraidah Abd. Wahab, The aim of this study is to develop an elastic modulus predictive model during unloading of plastically prestrained SPCC sheet steel. The model was developed using the back propagation neural networks (BPNN) based on the experimental tension unloading data. The method involves selecting the architecture, network parameters, training algorithm, and model validation. A comparison is carried out of the performance of BPNN and nonlinear regression methods. Results show the BPNN method can more accurately predict the elastic modulus at the respective prestrain levels. Fakulti Kejuruteraan ,UKM,Bangi. 2015 Article PeerReviewed application/pdf en http://journalarticle.ukm.my/9504/1/4.pdf M. R. Jamli, and A. K. Ariffin, and Dzuraidah Abd. Wahab, (2015) Modelling of elastic modulus degradation in sheet metal forming using back propagation neural network. Jurnal Kejuruteraan, 27 . pp. 23-28. ISSN 0128-0198 http://www.ukm.my/jkukm/?page_id=557
institution Universiti Kebangsaan Malaysia
building Perpustakaan Tun Sri Lanang Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Kebangsaan Malaysia
content_source UKM Journal Article Repository
url_provider http://journalarticle.ukm.my/
language English
description The aim of this study is to develop an elastic modulus predictive model during unloading of plastically prestrained SPCC sheet steel. The model was developed using the back propagation neural networks (BPNN) based on the experimental tension unloading data. The method involves selecting the architecture, network parameters, training algorithm, and model validation. A comparison is carried out of the performance of BPNN and nonlinear regression methods. Results show the BPNN method can more accurately predict the elastic modulus at the respective prestrain levels.
format Article
author M. R. Jamli,
A. K. Ariffin,
Dzuraidah Abd. Wahab,
spellingShingle M. R. Jamli,
A. K. Ariffin,
Dzuraidah Abd. Wahab,
Modelling of elastic modulus degradation in sheet metal forming using back propagation neural network
author_facet M. R. Jamli,
A. K. Ariffin,
Dzuraidah Abd. Wahab,
author_sort M. R. Jamli,
title Modelling of elastic modulus degradation in sheet metal forming using back propagation neural network
title_short Modelling of elastic modulus degradation in sheet metal forming using back propagation neural network
title_full Modelling of elastic modulus degradation in sheet metal forming using back propagation neural network
title_fullStr Modelling of elastic modulus degradation in sheet metal forming using back propagation neural network
title_full_unstemmed Modelling of elastic modulus degradation in sheet metal forming using back propagation neural network
title_sort modelling of elastic modulus degradation in sheet metal forming using back propagation neural network
publisher Fakulti Kejuruteraan ,UKM,Bangi.
publishDate 2015
url http://journalarticle.ukm.my/9504/1/4.pdf
http://journalarticle.ukm.my/9504/
http://www.ukm.my/jkukm/?page_id=557
_version_ 1643737820373712896
score 13.160551

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