• DocumentCode
    3726464
  • Title

    Interval Type-2 Recursive Fuzzy C-Means Clustering Algorithm in the TS Fuzzy Model Identification

  • Author

    Tanmoy Dam;Alok Kanti Deb

  • Author_Institution
    Electr. Eng. Dept., Indian Inst. of Technol. Kharagpur, Kharagpur, India
  • fYear
    2015
  • Firstpage
    22
  • Lastpage
    29
  • Abstract
    This paper presents an iterative Takagi Sugeno Fuzzy Model (TSFM) identification. Interval Type-2 Recursive Fuzzy C-Means (IT2RFCM) clustering algorithm has been used to classify the data space to obtain premise variable parameters and Weighted Recursive Least Square (WRLS) technique has been used to determine consequence parameters of each linear model. IT2RFCM clustering algorithm has been obtained from type-1 Fuzzy C-Means clustering algorithm by introducing fuzziness parameters. The effectiveness of the proposed IT2RFCM algorithm has been validated on Mackey-Glass time series data.
  • Keywords
    "Clustering algorithms","Heuristic algorithms","Fuzzy logic","Classification algorithms","Partitioning algorithms","Fuzzy set theory","Inference algorithms"
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence, 2015 IEEE Symposium Series on
  • Print_ISBN
    978-1-4799-7560-0
  • Type

    conf

  • DOI
    10.1109/SSCI.2015.14
  • Filename
    7376587
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=3726464