• DocumentCode
    1631854
  • Title

    Robust function approximation based on fuzzy sets and rough sets

  • Author

    Hsiao, Chih-Ching

  • Author_Institution
    Electr. Eng. Dept., Kao Yuan Univ., Kaohsiung, Taiwan
  • fYear
    2009
  • Firstpage
    1250
  • Lastpage
    1254
  • Abstract
    The rough set theory is successes to deal with imprecise, incomplete or uncertain for information system. Fuzzy set and the rough set theories turned out to be particularly adequate for the analysis of various types of data, especially, when dealing with inexact, uncertain or vague knowledge. In this paper, we propose an novel algorithm, which termed as rough-fuzzy c-regression model (RFCRM), that define fuzzy subspaces in a fuzzy regression manner and also include rough-set theory for TSK modeling with robust capability against outliers.
  • Keywords
    function approximation; fuzzy set theory; regression analysis; rough set theory; TSK modeling; fuzzy set theory; robust function approximation; rough set theory; rough-fuzzy c-regression model; Clustering algorithms; Degradation; Function approximation; Fuzzy sets; Least squares approximation; Robustness; Rough sets; Set theory; Training data; Working environment noise;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Fuzzy Systems, 2009. FUZZ-IEEE 2009. IEEE International Conference on
  • Conference_Location
    Jeju Island
  • ISSN
    1098-7584
  • Print_ISBN
    978-1-4244-3596-8
  • Electronic_ISBN
    1098-7584
  • Type

    conf

  • DOI
    10.1109/FUZZY.2009.5277427
  • Filename
    5277427