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다중 정상 하에서 단일 클래스 분류기법을 이용한 이상치 탐지 : TFT-LCD 공정 사례A Novelty Detection Algorithm for Multiple Normal Classes : Application to TFT-LCD Processes
- Other Titles
- A Novelty Detection Algorithm for Multiple Normal Classes : Application to TFT-LCD Processes
- Issue Date
- 2013
- Publisher
- 대한산업공학회
- Keywords
- Novelty Detection; Multiple Normal Classes; Mahalanobis Distance; Bootstrap Method; Data Mining; TFT-LCD Process
- Citation
- 대한산업공학회지, v.39, no.2, pp.82 - 89
- Indexed
- KCI
- Journal Title
- 대한산업공학회지
- Volume
- 39
- Number
- 2
- Start Page
- 82
- End Page
- 89
- ISSN
- 1225-0988
- Abstract
- Novelty 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.
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Related Researcher
- KIM, Seoung Bum
- College of Engineering (School of Industrial and Management Engineering)