• DocumentCode
    394166
  • Title

    Fuzzy mean point clustering neural network

  • Author

    Patil, P.M. ; Kulkarni, U.V. ; Sontakke, T.R.

  • Volume
    2
  • fYear
    2002
  • fDate
    18-22 Nov. 2002
  • Firstpage
    871
  • Abstract
    Fuzzy mean point clustering neural network (FMPCNN) is proposed with its learning algorithm, which utilizes fuzzy sets as pattern clusters. The performance of FMPCNN when verified with Fisher Iris data, it is found superior to Simpson´s fuzzy min-max neural network and fuzzy hyperline segment clustering neural network (FHLSCNN) proposed by Kulkarni and Sontakke.
  • Keywords
    fuzzy neural nets; fuzzy set theory; learning (artificial intelligence); pattern clustering; FMPCNN; Fisher Iris data; fuzzy hyperline segment clustering neural network; fuzzy mean point clustering neural network; fuzzy min-max neural network; fuzzy sets; learning algorithm; pattern clusters; Clustering algorithms; Computer science; Educational institutions; Fuzzy neural networks; Fuzzy sets; Iris; Network topology; Neural networks; Pattern clustering; Pattern recognition;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Information Processing, 2002. ICONIP '02. Proceedings of the 9th International Conference on
  • Print_ISBN
    981-04-7524-1
  • Type

    conf

  • DOI
    10.1109/ICONIP.2002.1198184
  • Filename
    1198184
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=394166