• DocumentCode
    723945
  • Title

    Approach to radiation temperature measuring and its application via support vector machine

  • Author

    Yan Ren ; Xiaomin Zhou ; Yanjun Lu ; Li Fu ; Rui Fang

  • Author_Institution
    Sch. of Autom., Shenyang Aerosp. Univ., Shenyang, China
  • fYear
    2015
  • fDate
    23-25 May 2015
  • Firstpage
    6476
  • Lastpage
    6479
  • Abstract
    This paper presents a measuring method based on Support Vector Machine(SVM), which is used to solve the high temperature measuring problem. As we all known, it is difficult to measure directly in complex industrial environment. Thus, the normal support vector machine(NOR-SVM) is improved, and then a new regression algorithm is proposed. Simulation results demonstrate that the improved algorithm has good nonlinear modeling, generalization ability and predictive ability. What´s more, this model needs less Support Vectors(SVs), so it learns more faster.
  • Keywords
    computerised instrumentation; regression analysis; support vector machines; temperature measurement; NOR-SVM; normal support vector machine; radiation temperature measurement; regression algorithm; Image color analysis; Mathematical model; Prediction algorithms; Predictive models; Support vector machines; Temperature measurement; Training; Learning Speed; Nonlinear Relationship; SVM; Temperature Measurement;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control and Decision Conference (CCDC), 2015 27th Chinese
  • Conference_Location
    Qingdao
  • Print_ISBN
    978-1-4799-7016-2
  • Type

    conf

  • DOI
    10.1109/CCDC.2015.7161985
  • Filename
    7161985