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...

Full description

Bibliographic Details
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/ http://journalarticle.ukm.my/9504/ http://journalarticle.ukm.my/9504/1/4.pdf

id	ukm-9504
recordtype	eprints
spelling	ukm-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
repository_type	Digital Repository
institution_category	Local University
institution	Universiti Kebangasaan Malaysia
building	UKM Institutional Repository
collection	Online Access
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/ http://journalarticle.ukm.my/9504/ http://journalarticle.ukm.my/9504/1/4.pdf
first_indexed	2023-09-18T19:55:04Z
last_indexed	2023-09-18T19:55:04Z
_version_	1777406474315628544

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

Similar Items