• DocumentCode
    296004
  • Title

    Fault modeling and reliability evaluations using artificial neural networks

  • Author

    Cheng, Chyun-Shin ; Hsu, Yen-Tseng ; Wu, Chwan-Chia

  • Author_Institution
    Dept. of Electr. Eng., Nat. Taiwan Univ., Taipei, Taiwan
  • Volume
    1
  • fYear
    1995
  • fDate
    Nov/Dec 1995
  • Firstpage
    427
  • Abstract
    In this paper, we present a generalized Markov reliability and fault-tolerant model (including the effects of permanent fault, transient fault and intermittent fault) for reliability evaluations based on the neural network techniques. The desired reliability of the system under design is fed to the neural network and when the neural network converges the parameters of the design are extracted from the weights of the neural network. We also obtained the simulation results which are in agreement with the classical analysis
  • Keywords
    Markov processes; failure analysis; fault tolerant computing; feedforward neural nets; reliability theory; Markov model; fault modeling; fault-tolerant model; feedforward neural networks; intermittent fault; permanent fault; reliability; transient fault; Analytical models; Artificial neural networks; Computational modeling; Computer network reliability; Fault tolerance; Feedforward neural networks; Feedforward systems; Neural networks; Neurons; Power system reliability;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks, 1995. Proceedings., IEEE International Conference on
  • Conference_Location
    Perth, WA
  • Print_ISBN
    0-7803-2768-3
  • Type

    conf

  • DOI
    10.1109/ICNN.1995.488139
  • Filename
    488139