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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Institution:	Universiti Kebangsaan Malaysia
Language:	English

id	my-ukm.journal.9504
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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

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

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