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

被引：2
作者：
Zhang R.-J. [1 ]
Yang W.-W. [1 ]
He Q. [1 ]
Wang X.-W. [1 ]
机构：
[1] School of Mechanical and Electrical Engineering, Shandong Jianzhu University, Fengming Road, Lingang Development District, Jinan, 250101, Shandong
来源：
International Journal of Industrial and Systems Engineering | 2016年 / 24卷 / 01期
关键词：
Bayesian network; Bucket elimination method; Electronic product; Joint probability; Reliability analysis;
D O I：
10.1504/IJISE.2016.078013
中图分类号：
学科分类号：
摘要：
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. Copyright © 2016 Inderscience Enterprises Ltd.
引用
收藏
页码：126 / 136
页数：10
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