• DocumentCode
    2752737
  • Title

    Modeling capability of type-1 fuzzy set and interval type-2 fuzzy set

  • Author

    Nie, Maowen ; Tan, Woei Wan

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Nat. Univ. of Singapore, Singapore, Singapore
  • fYear
    2012
  • fDate
    10-15 June 2012
  • Firstpage
    1
  • Lastpage
    8
  • Abstract
    Fuzzy logic (FL) has been regarded as a useful methodology in modelling. The modeling performance of FL heavily relies on the modeling capability of a fuzzy set (FS). However, the MF of a FS cannot be arbitrarily accurate in practice and thus the centroid as a measure of a FS cannot be accurate to any degree. In face of inaccurate MF, the sensitivity of the centroid of a FS to the deviation of its MF from the ideal MF determines the accuracy of the centroid. To evaluate the modeling capability of a type-1 (T1) FS and an interval type-2 (IT2) FS, this paper will present a comparative study of the sensitivity of the centroid of a T1 FS and an IT2 FS to the deviation of their MFs from the ideal MFs. In this paper, equations relating the amount that the centroid of a T1 FS and an IT2 FS vary with the deviation of their MFs from the ideal MFs were established. Based on the derived equations, it was found that an IT2 FS is able to provide an additional design freedom to vary the sensitivity of its centroid compared to a T1 FS. This unique characteristic may enable an IT2 FS to minimize the sensitivity of the centroid and thus to achieve higher modeling accuracy. Furthermore, guidelines for designing an IT2 FS were provided.
  • Keywords
    fuzzy logic; fuzzy set theory; FL; IT2 FS; T1 FS; additional design freedom; fuzzy logic; interval type-2 fuzzy set; modeling capability; sensitivity; type-1 fuzzy set; Accuracy; Computational modeling; Equations; Frequency modulation; Fuzzy logic; Sensitivity; Switches; Centroid; Interval type-2 fuzzy set; Karnik-Mendel type-reduction method; Modelling Capability;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Fuzzy Systems (FUZZ-IEEE), 2012 IEEE International Conference on
  • Conference_Location
    Brisbane, QLD
  • ISSN
    1098-7584
  • Print_ISBN
    978-1-4673-1507-4
  • Electronic_ISBN
    1098-7584
  • Type

    conf

  • DOI
    10.1109/FUZZ-IEEE.2012.6251178
  • Filename
    6251178