• DocumentCode
    3160986
  • Title

    Error separation base on small sample Bayesian network

  • Author

    Hui Fan ; Liwen Yan ; Peng Qiao ; Liu Han

  • Author_Institution
    Tianjin Key Lab. of High Speed Cutting & Precision Machining, Tianjin Univ. of Technol. & Educ., Tianjin, China
  • fYear
    2011
  • fDate
    8-10 Aug. 2011
  • Firstpage
    5545
  • Lastpage
    5548
  • Abstract
    Bayesian network (BN) method using in error separation is the hot issue of the current research. BN is a powerful tool for uncertainty reasoning and knowledge representation. When we use it combining with the statistical method, it shows a lot the advantage of data processing. This paper considers the many factors in measuring dynamic errors and of the complicated relationship, and brings the small sample BN into the measuring dynamic error separation. In view of the measurement error, we build the basic dependent relationships among variables and the basic construction among nodes and so on. Finally, we use simulation for experiment and analysis through the study of small sample BN.
  • Keywords
    Bayes methods; computerised instrumentation; error statistics; knowledge representation; measurement errors; statistical analysis; uncertainty handling; Bayesian network; data processing; error separation base; knowledge representation; measurement error; statistical method; uncertainty reasoning; Bayesian methods; Computer numerical control; Data models; Machine tools; Measurement uncertainty; Probability distribution; Bayesian network (BN); error separation; small sample;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Artificial Intelligence, Management Science and Electronic Commerce (AIMSEC), 2011 2nd International Conference on
  • Conference_Location
    Deng Leng
  • Print_ISBN
    978-1-4577-0535-9
  • Type

    conf

  • DOI
    10.1109/AIMSEC.2011.6009925
  • Filename
    6009925