Integration of artificial neural network and expert system for material classification of natural fibre reinforced polymer composites

Diversified choice of materials from natural fibre reinforced polymer composites with similar properties complicate the materials selection for engineering products. Implementation of expert system alone makes it difficult to scrutinize the vast selected materials. Hybrid of expert system with neura...

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Main Authors: Ahmed Ali, Basheer Ahmed, Salit, Mohd Sapuan, Zainudin, Edi Syams, Othman, Mohamed
Format: Article
Language:English
Published: Science Publications 2015
Online Access:http://psasir.upm.edu.my/id/eprint/13992/1/13992.pdf
http://psasir.upm.edu.my/id/eprint/13992/
http://thescipub.com/abstract/10.3844/ajassp.2015.174.184
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Institution: Universiti Putra Malaysia
Language: English
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spelling my.upm.eprints.139922018-09-04T04:31:53Z http://psasir.upm.edu.my/id/eprint/13992/ Integration of artificial neural network and expert system for material classification of natural fibre reinforced polymer composites Ahmed Ali, Basheer Ahmed Salit, Mohd Sapuan Zainudin, Edi Syams Othman, Mohamed Diversified choice of materials from natural fibre reinforced polymer composites with similar properties complicate the materials selection for engineering products. Implementation of expert system alone makes it difficult to scrutinize the vast selected materials. Hybrid of expert system with neural network technology is desired. Classification of material through neural network under various criteria influences the decision in narrowing down the selection. In this study, the integration of artificial neural network with expert system for material classification is explored. The computational tool Matlab is proposed for classification and the materials focused were natural fibre composites. Levenberg-Marquardt training algorithm, which provides faster rate of convergence, is applied for training the feed forward network. The system proves to be consistant with 93.3% classification accuracy with 15 neurons in the hidden layer. The validation of the output is compared with the target on the basis of desired mechanical properties of natural fibre reinforced polymer composites for automotive interior components. Science Publications 2015 Article PeerReviewed text en http://psasir.upm.edu.my/id/eprint/13992/1/13992.pdf Ahmed Ali, Basheer Ahmed and Salit, Mohd Sapuan and Zainudin, Edi Syams and Othman, Mohamed (2015) Integration of artificial neural network and expert system for material classification of natural fibre reinforced polymer composites. American Journal of Applied Sciences, 12 (3). pp. 174-184. ISSN 1546-9239; ESSN: 1554-3641 http://thescipub.com/abstract/10.3844/ajassp.2015.174.184 10.3844/ajassp.2015.174.184
institution Universiti Putra Malaysia
building UPM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Putra Malaysia
content_source UPM Institutional Repository
url_provider http://psasir.upm.edu.my/
language English
description Diversified choice of materials from natural fibre reinforced polymer composites with similar properties complicate the materials selection for engineering products. Implementation of expert system alone makes it difficult to scrutinize the vast selected materials. Hybrid of expert system with neural network technology is desired. Classification of material through neural network under various criteria influences the decision in narrowing down the selection. In this study, the integration of artificial neural network with expert system for material classification is explored. The computational tool Matlab is proposed for classification and the materials focused were natural fibre composites. Levenberg-Marquardt training algorithm, which provides faster rate of convergence, is applied for training the feed forward network. The system proves to be consistant with 93.3% classification accuracy with 15 neurons in the hidden layer. The validation of the output is compared with the target on the basis of desired mechanical properties of natural fibre reinforced polymer composites for automotive interior components.
format Article
author Ahmed Ali, Basheer Ahmed
Salit, Mohd Sapuan
Zainudin, Edi Syams
Othman, Mohamed
spellingShingle Ahmed Ali, Basheer Ahmed
Salit, Mohd Sapuan
Zainudin, Edi Syams
Othman, Mohamed
Integration of artificial neural network and expert system for material classification of natural fibre reinforced polymer composites
author_facet Ahmed Ali, Basheer Ahmed
Salit, Mohd Sapuan
Zainudin, Edi Syams
Othman, Mohamed
author_sort Ahmed Ali, Basheer Ahmed
title Integration of artificial neural network and expert system for material classification of natural fibre reinforced polymer composites
title_short Integration of artificial neural network and expert system for material classification of natural fibre reinforced polymer composites
title_full Integration of artificial neural network and expert system for material classification of natural fibre reinforced polymer composites
title_fullStr Integration of artificial neural network and expert system for material classification of natural fibre reinforced polymer composites
title_full_unstemmed Integration of artificial neural network and expert system for material classification of natural fibre reinforced polymer composites
title_sort integration of artificial neural network and expert system for material classification of natural fibre reinforced polymer composites
publisher Science Publications
publishDate 2015
url http://psasir.upm.edu.my/id/eprint/13992/1/13992.pdf
http://psasir.upm.edu.my/id/eprint/13992/
http://thescipub.com/abstract/10.3844/ajassp.2015.174.184
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