• DocumentCode
    2972078
  • Title

    A support vector machine-based pattern recognizer using selected features for control chart patterns analysis

  • Author

    Cheng, C.S. ; Cheng, H.P. ; Huang, K.K.

  • Author_Institution
    Dept. of Ind. Eng. & Manage., Yuan-Ze Univ., Nei-Li, Taiwan
  • fYear
    2009
  • fDate
    8-11 Dec. 2009
  • Firstpage
    419
  • Lastpage
    423
  • Abstract
    In this paper we review two implementation modes of control chart pattern recognition and introduce a new research problem concerning pattern displacement problem in the ¿recognition only when necessary¿ mode. A set of features are developed by taking the pattern displacement into account. Simulation studies indicate that an SVM-based pattern recognizer with features as input vector performs significantly better than that of using raw data as inputs.
  • Keywords
    control charts; pattern recognition; statistical process control; support vector machines; control chart patterns analysis; pattern recognizer; statistical process control; support vector machine; Artificial neural networks; Control charts; Data mining; Feature extraction; Monitoring; Pattern analysis; Pattern recognition; Stability; Support vector machines; Testing; SVM; features; pattern recognition;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Industrial Engineering and Engineering Management, 2009. IEEM 2009. IEEE International Conference on
  • Conference_Location
    Hong Kong
  • Print_ISBN
    978-1-4244-4869-2
  • Electronic_ISBN
    978-1-4244-4870-8
  • Type

    conf

  • DOI
    10.1109/IEEM.2009.5373318
  • Filename
    5373318
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2972078