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...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Fakulti Kejuruteraan ,UKM,Bangi.
2015
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| Online Access: | http://journalarticle.ukm.my/9504/ http://journalarticle.ukm.my/9504/1/4.pdf |
| _version_ | 1848812109801979904 |
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| author | M. R. Jamli, A. K. Ariffin, Dzuraidah Abd. Wahab, |
| author_facet | M. R. Jamli, A. K. Ariffin, Dzuraidah Abd. Wahab, |
| author_sort | M. R. Jamli, |
| building | UKM Institutional Repository |
| collection | Online Access |
| 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. |
| first_indexed | 2025-11-14T23:57:04Z |
| format | Article |
| id | oai:generic.eprints.org:9504 |
| institution | Universiti Kebangasaan Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-14T23:57:04Z |
| publishDate | 2015 |
| publisher | Fakulti Kejuruteraan ,UKM,Bangi. |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | oai:generic.eprints.org: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 |
| spellingShingle | M. R. Jamli, A. K. Ariffin, Dzuraidah Abd. Wahab, Modelling of elastic modulus degradation in sheet metal forming using back propagation neural network |
| title | 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_short | 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 |
| url | http://journalarticle.ukm.my/9504/ http://journalarticle.ukm.my/9504/ http://journalarticle.ukm.my/9504/1/4.pdf |