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Bayesian System Reliability Assessment Method with Maximum Entropy as Prior Distribution

机译:以最大熵为先验分布的贝叶斯系统可靠性评估方法

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摘要

Bayesian system reliability assessment method with maximum entropy as prior distribution is developed in the present analysis. The system reliability assessment model is established, and the method and process of system reliability assessment are put forward. The method is based on the theory of information entropy. The probability density function and distribution function of system reliability parameters are given by using maximum entropy method. Prior distribution of Bayesian analysis method is the distribution function. Likelihood function is given by a small amount of field test data. According to Bayesian methods, posterior distribution is determined by using prior distribution and likelihood function. The point estimation and interval estimation of system reliability parameters are calculated in order to evaluate the system reliability. The method solves better the problem of system reliability assessment for small sample cases, and is an optimum method for reliability assessment of large and complex systems.
机译:本分析提出了一种具有最大熵作为先验分布的贝叶斯系统可靠性评估方法。建立了系统可靠性评估模型,提出了系统可靠性评估的方法和过程。该方法基于信息熵理论。利用最大熵法给出了系统可靠性参数的概率密度函数和分布函数。贝叶斯分析方法的先验分布是分布函数。可能性函数由少量的现场测试数据提供。根据贝叶斯方法,通过使用先验分布和似然函数确定后验分布。计算系统可靠性参数的点估计和间隔估计,以评估系统可靠性。该方法较好地解决了小样本情况下系统可靠性评估的问题,是大型复杂系统可靠性评估的最佳方法。

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