Neural network-based prediction models for physical properties of oil palm medium density fiberboard / Faridah Sh. Ismail

Medium Density Fiberboard (MDF) is an alternative to solid wood used in furniture industries. As an engineered wood, MDF needs to establish the strength level to guarantee its quality. The test procedures for mechanical and physical properties of MDF should conform to a specified standard, prior to...

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Bibliographic Details
Main Author:	Sh. Ismail, Faridah
Format:	Book Section
Language:	English
Published:	Institute of Graduate Studies, UiTM 2015
Subjects:	Malaysia
Online Access:	http://ir.uitm.edu.my/id/eprint/19440/ http://ir.uitm.edu.my/id/eprint/19440/1/ABS_FARIDAH%20SH.%20ISMAIL%20TDRA%20VOL%208%20IGS%2015.pdf

id	uitm-19440
recordtype	eprints
spelling	uitm-194402018-06-11T07:49:20Z http://ir.uitm.edu.my/id/eprint/19440/ Neural network-based prediction models for physical properties of oil palm medium density fiberboard / Faridah Sh. Ismail Sh. Ismail, Faridah Malaysia Medium Density Fiberboard (MDF) is an alternative to solid wood used in furniture industries. As an engineered wood, MDF needs to establish the strength level to guarantee its quality. The test procedures for mechanical and physical properties of MDF should conform to a specified standard, prior to releasing processed fiberboards for manufacturing. These tests are costly for they involve a high amount of resources, especially to research institutions. The primary aim of this research is to reduce testing time of three lengthy procedures; namely, 24-hour thickness swelling, 24-hour water absorption and 48-hour moisture content. An intelligent predictive model will replace the lengthy procedures by predicting the properties using known fiberboard characteristics. Back-propagation algorithm is a training method widely used in a multilayer perceptron Neural Network model. It optimizes random values for network weights and biases. However, the result normally faces local optima problems. This situation can be solved by embedding Genetic Algorithm (GA) in the network to replace back-propagation method… Institute of Graduate Studies, UiTM 2015 Book Section PeerReviewed text en http://ir.uitm.edu.my/id/eprint/19440/1/ABS_FARIDAH%20SH.%20ISMAIL%20TDRA%20VOL%208%20IGS%2015.pdf Sh. Ismail, Faridah (2015) Neural network-based prediction models for physical properties of oil palm medium density fiberboard / Faridah Sh. Ismail. In: The Doctoral Research Abstracts. IGS Biannual Publication, 8 (8). Institute of Graduate Studies, UiTM, Shah Alam.
repository_type	Digital Repository
institution_category	Local University
institution	Universiti Teknologi MARA
building	UiTM Institutional Repository
collection	Online Access
language	English
topic	Malaysia
spellingShingle	Malaysia Sh. Ismail, Faridah Neural network-based prediction models for physical properties of oil palm medium density fiberboard / Faridah Sh. Ismail
description	Medium Density Fiberboard (MDF) is an alternative to solid wood used in furniture industries. As an engineered wood, MDF needs to establish the strength level to guarantee its quality. The test procedures for mechanical and physical properties of MDF should conform to a specified standard, prior to releasing processed fiberboards for manufacturing. These tests are costly for they involve a high amount of resources, especially to research institutions. The primary aim of this research is to reduce testing time of three lengthy procedures; namely, 24-hour thickness swelling, 24-hour water absorption and 48-hour moisture content. An intelligent predictive model will replace the lengthy procedures by predicting the properties using known fiberboard characteristics. Back-propagation algorithm is a training method widely used in a multilayer perceptron Neural Network model. It optimizes random values for network weights and biases. However, the result normally faces local optima problems. This situation can be solved by embedding Genetic Algorithm (GA) in the network to replace back-propagation method…
format	Book Section
author	Sh. Ismail, Faridah
author_facet	Sh. Ismail, Faridah
author_sort	Sh. Ismail, Faridah
title	Neural network-based prediction models for physical properties of oil palm medium density fiberboard / Faridah Sh. Ismail
title_short	Neural network-based prediction models for physical properties of oil palm medium density fiberboard / Faridah Sh. Ismail
title_full	Neural network-based prediction models for physical properties of oil palm medium density fiberboard / Faridah Sh. Ismail
title_fullStr	Neural network-based prediction models for physical properties of oil palm medium density fiberboard / Faridah Sh. Ismail
title_full_unstemmed	Neural network-based prediction models for physical properties of oil palm medium density fiberboard / Faridah Sh. Ismail
title_sort	neural network-based prediction models for physical properties of oil palm medium density fiberboard / faridah sh. ismail
publisher	Institute of Graduate Studies, UiTM
publishDate	2015
url	http://ir.uitm.edu.my/id/eprint/19440/ http://ir.uitm.edu.my/id/eprint/19440/1/ABS_FARIDAH%20SH.%20ISMAIL%20TDRA%20VOL%208%20IGS%2015.pdf
first_indexed	2023-09-18T23:02:34Z
last_indexed	2023-09-18T23:02:34Z
_version_	1777418271147950080

Neural network-based prediction models for physical properties of oil palm medium density fiberboard / Faridah Sh. Ismail

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