Article: Genetic algorithm based defect identification system

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TitleGenetic algorithm based defect identification system
AuthorsTam, SM1
Cheung, KC1
Issue Date2000
PublisherPergamon. The Journal's web site is located at http://www.elsevier.com/locate/eswa
CitationExpert Systems With Applications, 2000, v. 18 n. 1, p. 17-25 [How to Cite?]
DOI: http://dx.doi.org/10.1016/S0957-4174(99)00046-9
AbstractA genetic algorithm based defect identification system for machined-parts inspection purposes is developed. It can identify defects from the mass and coordinates of center of mass of a defective part. This method uses genetic algorithm search to find combinations of dimensions that produce the same mass and coordinates of center of mass as the defective part. There is also a knowledge base to store defects that have been identified previously.
ISSN0957-4174
2011 Impact Factor: 2.203
2011 SCImago Journal Rankings: 0.070
DOIhttp://dx.doi.org/10.1016/S0957-4174(99)00046-9
ISI Accession Number IDWOS:000084945500002
ReferencesReferences in Scopus
DC Field
Value
dc.contributor.authorTam, SM
dc.contributor.authorCheung, KC
dc.date.accessioned2012-08-08T08:42:51Z
dc.date.available2012-08-08T08:42:51Z
dc.date.issued2000
dc.description.abstractA genetic algorithm based defect identification system for machined-parts inspection purposes is developed. It can identify defects from the mass and coordinates of center of mass of a defective part. This method uses genetic algorithm search to find combinations of dimensions that produce the same mass and coordinates of center of mass as the defective part. There is also a knowledge base to store defects that have been identified previously.
dc.description.natureLink_to_subscribed_fulltext
dc.identifier.citationExpert Systems With Applications, 2000, v. 18 n. 1, p. 17-25 [How to Cite?]
DOI: http://dx.doi.org/10.1016/S0957-4174(99)00046-9
dc.identifier.doihttp://dx.doi.org/10.1016/S0957-4174(99)00046-9
dc.identifier.epage25
dc.identifier.isiWOS:000084945500002
dc.identifier.issn0957-4174
2011 Impact Factor: 2.203
2011 SCImago Journal Rankings: 0.070
dc.identifier.issue1
dc.identifier.scopuseid_2-s2.0-0033689774
dc.identifier.spage17
dc.identifier.urihttp://hdl.handle.net/10722/156537
dc.identifier.volume18
dc.languageeng
dc.publisherPergamon. The Journal's web site is located at http://www.elsevier.com/locate/eswa
dc.publisher.placeUnited Kingdom
dc.relation.ispartofExpert Systems with Applications
dc.relation.referencesReferences in Scopus
dc.titleGenetic algorithm based defect identification system
dc.typeArticle
Author Affiliations
  1. The University of Hong Kong