• DocumentCode
    1564371
  • Title

    Monitoring Approach Using Recurrent Radial Basis Function Neural Networks and Neuro-Fuzzy Systems

  • Author

    Racoceanu, Daniel ; Zerhouni, Noureddine

  • Author_Institution
    Dept. of Sci., Franche-Comte Univ., Besancon
  • Volume
    2
  • fYear
    2005
  • Firstpage
    678
  • Lastpage
    682
  • Abstract
    Multiple reconfiguration and complexity of modern production systems lead to design intelligent monitoring aid systems. The use of artificial intelligence techniques in order to exploit their learning and human experience modeling seems very promising. In this paper, we propose a new monitoring aid system composed by a dynamic neural network detection tool and a neuro-fuzzy diagnosis tool. Learning capabilities due to the neural structure permit us to update the monitoring aid system. The neuro-fuzzy network provides an abductive diagnosis. Moreover it takes into account the uncertainties on the maintenance knowledge by giving a fuzzy characterization of each cause
  • Keywords
    computerised monitoring; production engineering computing; radial basis function networks; recurrent neural nets; abductive diagnosis; artificial intelligence techniques; dynamic neural network detection tool; intelligent monitoring aid systems; modern production systems; neuro-fuzzy diagnosis tool; recurrent radial basis function neural networks; Artificial intelligence; Artificial neural networks; Fuzzy neural networks; Humans; Intelligent systems; Learning; Monitoring; Production systems; Radial basis function networks; Uncertainty;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks and Brain, 2005. ICNN&B '05. International Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    0-7803-9422-4
  • Type

    conf

  • DOI
    10.1109/ICNNB.2005.1614721
  • Filename
    1614721