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Joint probability inference algorithms of a Bayesian network and reliability analysis of electronic products

Author

Listed:
  • Rui-Jun Zhang
  • Wei-wei Yang
  • Qin He
  • Xiao-wei Wang

Abstract

Considering the tedious and complex problem of solving joint probability with the bucket elimination algorithm, a parallel joint probability inference algorithm was proposed. The logical relation was analysed among each node variable and the inverse order method of the bucket elimination was used to introduce the mathematical expressions of joint probability and calculate the probabilities of one or more node failures when the network fails. The method is applied into the example of reliable analysis of electronic products and is demonstrated the simplicity and effectiveness of the method in the process of two-way Bayesian network inference. The results can be used to identify the weak links of electronic products and also provide a theoretical basis for reliability and maintenance strategies for electronic products.

Suggested Citation

  • Rui-Jun Zhang & Wei-wei Yang & Qin He & Xiao-wei Wang, 2016. "Joint probability inference algorithms of a Bayesian network and reliability analysis of electronic products," International Journal of Industrial and Systems Engineering, Inderscience Enterprises Ltd, vol. 24(1), pages 126-136.
    • Handle: RePEc:ids:ijisen:v:24:y:2016:i:1:p:126-136
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