• DocumentCode
    313609
  • Title

    A fuzzy neural network based on hierarchical space partitioning

  • Author

    Kwong Chak, Chu ; Feng, Gang ; Palaniswami, Marimuthu

  • Author_Institution
    Dept. of Electr. & Electron. Eng., Melbourne Univ., Vic., Australia
  • Volume
    1
  • fYear
    1997
  • fDate
    9-12 Jun 1997
  • Firstpage
    414
  • Abstract
    A self-organized and adaptive fuzzy system implemented in the framework of sigmoid function neural networks is proposed. The proposed fuzzy neural network adopts the hierarchical space partitioning method so that it can generate its rules and optimize its membership functions by its hybrid algorithm. Simulation is presented to demonstrate the performance of the proposed scheme
  • Keywords
    adaptive systems; fuzzy neural nets; fuzzy systems; learning (artificial intelligence); logic partitioning; neural net architecture; adaptive fuzzy system; architecture; fuzzy neural network; hierarchical space partitioning; learning algorithm; membership functions; self-organized systems; sigmoid function neural networks; Adaptive systems; Fuzzy neural networks; Fuzzy sets; Fuzzy systems; Hybrid power systems; Neural networks; Neurons; Optimization methods; Partitioning algorithms; Takagi-Sugeno model;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks,1997., International Conference on
  • Conference_Location
    Houston, TX
  • Print_ISBN
    0-7803-4122-8
  • Type

    conf

  • DOI
    10.1109/ICNN.1997.611704
  • Filename
    611704
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=313609