Bayesian network approach to classify damages and f -folds feature subset selection method in laminated composite materials

Citation

Mohamed Addin, Addin Osman and Salit, Mohd Sapuan and Ebrahimi, Mahdi and Othman, Mohamed and Ismail, Napsiah (2005) Bayesian network approach to classify damages and f -folds feature subset selection method in laminated composite materials. In: International Advanced Technology Congress: Conference on Intelligent Systems and Robotics, 6-8 Dec. 2005, Putrajaya, Malaysia. .

Abstract

This paper is intended to introduce the Bayesian network in general and the Naïve-bayes in particular as one of the most successful classification systems to simulate damage detection in laminated composite materials. A method for feature subset selection based on intervals between the amplitudes of waves used for damage detection is also introduced. The method utilizes clustering in the process of feature subset selection. The Bayesian classification and the feature selection method are analyzed based on theoretical point of view and only preliminary tests were conducted based on artificial damages created in quasi-isotopic laminates of the AS4/3501-6 graphite/epoxy system.

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Additional Metadata

Item Type:	Conference or Workshop Item (Paper)
Divisions:	Faculty of Computer Science and Information Technology Faculty of Engineering Institute of Advanced Technology
Keywords:	Bayesian network; Laminated composite materials
Depositing User:	Erni Suraya Abdul Aziz
Date Deposited:	13 Jul 2015 07:21
Last Modified:	13 Jul 2015 07:21
URI:	http://psasir.upm.edu.my/id/eprint/38990
Statistic Details:	View Download Statistic

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