Detailed Information

Cited 0 time in webofscience Cited 0 time in scopus
Metadata Downloads

다중 정상 하에서 단일 클래스 분류기법을 이용한 이상치 탐지 : TFT-LCD 공정 사례

Full metadata record
DC Field Value Language
dc.contributor.author주태우-
dc.contributor.author김성범-
dc.date.accessioned2021-09-06T09:16:37Z-
dc.date.available2021-09-06T09:16:37Z-
dc.date.created2021-06-17-
dc.date.issued2013-
dc.identifier.issn1225-0988-
dc.identifier.urihttps://scholar.korea.ac.kr/handle/2021.sw.korea/105715-
dc.description.abstractNovelty detection (ND) is an effective technique that can be used to determine whether a future observation is normal or not. In the present study we propose a novelty detection algorithm that can handle a situation where the distributions of target (normal) observations are inhomogeneous. A simulation study and a real case with the TFT-LCD process demonstrated the effectiveness and usefulness of the proposed algorithm.-
dc.languageKorean-
dc.language.isoko-
dc.publisher대한산업공학회-
dc.title다중 정상 하에서 단일 클래스 분류기법을 이용한 이상치 탐지 : TFT-LCD 공정 사례-
dc.title.alternativeA Novelty Detection Algorithm for Multiple Normal Classes : Application to TFT-LCD Processes-
dc.typeArticle-
dc.contributor.affiliatedAuthor김성범-
dc.identifier.doi10.7232/JKIIE.2013.39.2.082-
dc.identifier.bibliographicCitation대한산업공학회지, v.39, no.2, pp.82 - 89-
dc.relation.isPartOf대한산업공학회지-
dc.citation.title대한산업공학회지-
dc.citation.volume39-
dc.citation.number2-
dc.citation.startPage82-
dc.citation.endPage89-
dc.type.rimsART-
dc.identifier.kciidART001760420-
dc.description.journalClass2-
dc.description.journalRegisteredClasskci-
dc.subject.keywordAuthorNovelty Detection-
dc.subject.keywordAuthorMultiple Normal Classes-
dc.subject.keywordAuthorMahalanobis Distance-
dc.subject.keywordAuthorBootstrap Method-
dc.subject.keywordAuthorData Mining-
dc.subject.keywordAuthorTFT-LCD Process-
Files in This Item
There are no files associated with this item.
Appears in
Collections
College of Engineering > School of Industrial and Management Engineering > 1. Journal Articles

qrcode

Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.

Related Researcher

Researcher KIM, Seoung Bum photo

KIM, Seoung Bum
College of Engineering (School of Industrial and Management Engineering)
Read more

Altmetrics

Total Views & Downloads

BROWSE