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Reliability analysis of a consecutive r-out-of-n: F system based on neural networks

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  • Habib, Aziz
  • Alsieidi, Ragab
  • Youssef, Ghada

Abstract

In this paper, we present a generalized Markov reliability and fault-tolerant model, which includes the effects of permanent fault and intermittent fault for reliability evaluations based on neural network techniques. The reliability of a consecutive r-out-of-n: F system was obtained with a three-layer connected neural network represents a discrete time state reliability Markov model of the system. Such that we fed the neural network with the desired reliability of the system under design. Then we extracted the parameters of the system from the neural weights at the convergence of the neural network to the desired reliability. Finally, we obtain simulation results.

Suggested Citation

  • Habib, Aziz & Alsieidi, Ragab & Youssef, Ghada, 2009. "Reliability analysis of a consecutive r-out-of-n: F system based on neural networks," Chaos, Solitons & Fractals, Elsevier, vol. 39(2), pages 610-624.
    • Handle: RePEc:eee:chsofr:v:39:y:2009:i:2:p:610-624
    DOI: 10.1016/j.chaos.2007.01.151
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    Cited by:

    1. Mellal, Mohamed Arezki & Al-Dahidi, Sameer & Williams, Edward J., 2020. "System reliability optimization with heterogeneous components using hosted cuckoo optimization algorithm," Reliability Engineering and System Safety, Elsevier, vol. 203(C).
    2. Cai, Baoping & Liu, Yonghong & Ma, Yunpeng & Huang, Lei & Liu, Zengkai, 2015. "A framework for the reliability evaluation of grid-connected photovoltaic systems in the presence of intermittent faults," Energy, Elsevier, vol. 93(P2), pages 1308-1320.

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