한국경영과학회:학술대회논문집 (Proceedings of the Korean Operations and Management Science Society Conference)

한국경영과학회 (The Korean Operations Research and Management Science Society)
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Using Artificial Neural Networks to detect Variance Change Point for Data Separation

  • Han Young-Chul (Department of Information and Industrial Engineering, Yonsei University) ;
  • Oh Kyong-Joo (Department of Information and Industrial Engineering, Yonsei University) ;
  • Kim Tae-Yoon (Department of Statistics, Keimyung University)
  • 발행 : 2006.05.01
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초록

In this article, it will be shown that a nonparametric and data-adaptive approach to the variance change point (VCP) detection problem is possible by formulating it as a pattern classification problem. Technical aspects of the VCP detector are discussed, which include its training strategy and selection of proper classification tool.

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