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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
2013 Impact Factor: 1.965
2013 SCImago Journal Rankings: 1.487
 
DOIhttp://dx.doi.org/10.1016/S0957-4174(99)00046-9
 
ISI Accession Number IDWOS:000084945500002
 
ReferencesReferences in Scopus
 
DC FieldValue
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
2013 Impact Factor: 1.965
2013 SCImago Journal Rankings: 1.487
 
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
 
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Author Affiliations
  1. The University of Hong Kong