• DocumentCode
    3737490
  • Title

    Study on kernel partial least squares based key indicator prediction

  • Author

    Shen Yin;Mingyu Wang;Hao Luo;Huijun Gao

  • Author_Institution
    Research Institute of Intelligent Control and Systems, Harbin Institute of Technology, Harbin, Heilongjiang, 150001, China
  • fYear
    2015
  • Firstpage
    3016
  • Lastpage
    3021
  • Abstract
    Kernel method has been applied to many multivariate statistical analysis techniques. In this paper, we investigated the regression properties of Kernel Partial Least Squares (KPLS) and compared it to the standard technique. Basic mathematical algorithms and application of KPLS were shown. We further established regression model based on KPLS and demonstrated the model by a numerical case.
  • Keywords
    "Yttrium","Kernel","Principal component analysis","Input variables","Mathematical model","Standards"
  • Publisher
    ieee
  • Conference_Titel
    Industrial Electronics Society, IECON 2015 - 41st Annual Conference of the IEEE
  • Type

    conf

  • DOI
    10.1109/IECON.2015.7392562
  • Filename
    7392562
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=3737490