• DocumentCode
    325158
  • Title

    Possibility data analysis with rough sets concept

  • Author

    Tanaka, Hideo ; Lee, Haekwan ; Guo, Peijun

  • Author_Institution
    Dept. of Ind. Eng., Osaka Prefectural Univ., Sakai, Japan
  • Volume
    1
  • fYear
    1998
  • fDate
    4-9 May 1998
  • Firstpage
    117
  • Abstract
    This paper is dealing with the upper and lower approximation models for representing the given phenomenon in a fuzzy environment as data analysis. The upper and lower approximation models can be derived from the given data with the possibility and necessity concepts, respectively. Thus, the given phenomenon can be analyzed as two approximation models which represent the upper and lower analyses for the given data. The modalities of the upper and lower models have been illustrated in regression analysis and also in the identification methods of possibility distributions. The comparison of the concepts of possibility data analysis and rough sets is shown clearly. A measure similar to the accuracy measure of rough sets is used to clarify the difference between the data structure and the assumed model
  • Keywords
    approximation theory; data analysis; data structures; fuzzy set theory; modelling; possibility theory; statistical analysis; approximation models; data envelopment analysis; data structure; fuzzy set theory; identification; lower models; possibility data analysis; regression analysis; rough sets; upper models; Data analysis; Data structures; Industrial engineering; Linear regression; Portfolios; Possibility theory; Regression analysis; Rough sets; Uncertainty; Vectors;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Fuzzy Systems Proceedings, 1998. IEEE World Congress on Computational Intelligence., The 1998 IEEE International Conference on
  • Conference_Location
    Anchorage, AK
  • ISSN
    1098-7584
  • Print_ISBN
    0-7803-4863-X
  • Type

    conf

  • DOI
    10.1109/FUZZY.1998.687469
  • Filename
    687469