Dominant feature identification for industrial fault detection and isolation applications

10.1016/j.eswa.2011.01.160

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Bibliographic Details
Main Authors:	Zhou, J.-H., Pang, C.K., Lewis, F.L., Zhong, Z.-W.
Other Authors:	ELECTRICAL & COMPUTER ENGINEERING
Format:	Article
Published:	2014
Subjects:	Least Square Error (LSE) Neural Network (NN) Principal Component Analysis (PCA) Principal Feature Analysis (PFA) Singular Value Decomposition (SVD)
Online Access:	http://scholarbank.nus.edu.sg/handle/10635/55691
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Institution:	National University of Singapore

id	sg-nus-scholar.10635-55691
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spelling	sg-nus-scholar.10635-556912023-10-26T20:09:51Z Dominant feature identification for industrial fault detection and isolation applications Zhou, J.-H. Pang, C.K. Lewis, F.L. Zhong, Z.-W. ELECTRICAL & COMPUTER ENGINEERING Least Square Error (LSE) Neural Network (NN) Principal Component Analysis (PCA) Principal Feature Analysis (PFA) Singular Value Decomposition (SVD) 10.1016/j.eswa.2011.01.160 Expert Systems with Applications 38 8 10676-10684 ESAPE 2014-06-17T02:46:01Z 2014-06-17T02:46:01Z 2011-08 Article Zhou, J.-H., Pang, C.K., Lewis, F.L., Zhong, Z.-W. (2011-08). Dominant feature identification for industrial fault detection and isolation applications. Expert Systems with Applications 38 (8) : 10676-10684. ScholarBank@NUS Repository. https://doi.org/10.1016/j.eswa.2011.01.160 09574174 http://scholarbank.nus.edu.sg/handle/10635/55691 000290237500185 Scopus
institution	National University of Singapore
building	NUS Library
continent	Asia
country	Singapore Singapore
content_provider	NUS Library
collection	ScholarBank@NUS
topic	Least Square Error (LSE) Neural Network (NN) Principal Component Analysis (PCA) Principal Feature Analysis (PFA) Singular Value Decomposition (SVD)
spellingShingle	Least Square Error (LSE) Neural Network (NN) Principal Component Analysis (PCA) Principal Feature Analysis (PFA) Singular Value Decomposition (SVD) Zhou, J.-H. Pang, C.K. Lewis, F.L. Zhong, Z.-W. Dominant feature identification for industrial fault detection and isolation applications
description	10.1016/j.eswa.2011.01.160
author2	ELECTRICAL & COMPUTER ENGINEERING
author_facet	ELECTRICAL & COMPUTER ENGINEERING Zhou, J.-H. Pang, C.K. Lewis, F.L. Zhong, Z.-W.
format	Article
author	Zhou, J.-H. Pang, C.K. Lewis, F.L. Zhong, Z.-W.
author_sort	Zhou, J.-H.
title	Dominant feature identification for industrial fault detection and isolation applications
title_short	Dominant feature identification for industrial fault detection and isolation applications
title_full	Dominant feature identification for industrial fault detection and isolation applications
title_fullStr	Dominant feature identification for industrial fault detection and isolation applications
title_full_unstemmed	Dominant feature identification for industrial fault detection and isolation applications
title_sort	dominant feature identification for industrial fault detection and isolation applications
publishDate	2014
url	http://scholarbank.nus.edu.sg/handle/10635/55691
_version_	1781412173261570048

Dominant feature identification for industrial fault detection and isolation applications

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