无失效数据情形可靠性参数的估计和调整

本文在无失效取样情形下,提出了产品可靠性参数的一种估计和调整的方法———加权多层Bayes估计法.在无失效数据情形下失效率的多层Bayes估计和引进失效信息后失效率的多层Bayes估计的基础上,对可靠性参数进行了估计和调整———给出了失效率和可靠度的加权多层Bayes估计.最后,结合发动机的实际问题进行了计算,结果表明本文提出的方法可行且便于应用.     

无失效数据的Bayes和多层Bayes分析

本文推广了文献[6]的结果，对指数分布无失效数据的失效率，给出了Bayes估计、Bayes置信上限以及多层Bayes估计，从而可以得到无失效数据可靠度的估计，最后，结合实际问题进行了计算。     

无失效数据失效概率的Bayes估计

本文对无失效数据(ti,ni)在ti 时刻的失效概率pi= P｛T< ti｝的先验密度的核为(1- pi)k时,给出了pi 的Bayes估计和多层Bayes估计,由此可以得到无失效数据可靠度的估计.最后,结合实际问题进行了计算.     

无失效数据情形参数的综合估计

本对指数分布的无失效数据,在引进失效信息后,在先验分布为Gamma分布时,给出了失效率的多层Bayes估计和综合Bayes估计,并给出了无失效数据情形可靠度的综合估计,还结合实际问题进行了计算。     

基于无失效数据的可靠度的估计

对二项分布无失效数据，在可靠度的先验密度为且时，给出了可靠度的多层Bayes估计．     

无失效数据的Bayes和多层Bayes估计

对无失效数据的研究 ,是近些年来遇到的一个新问题 ,在实际问题中迫切需要解决 ,这项工作具有理论和实际应用价值 .本文对无失效数据 (ti,ni) ,在时刻ti 的失效概率pi=p{T 相似文献   

无失效数据情形失效率的综合估计

对指数分布的无失效数据，提出了无失效数据情形失效率的综合估计法。在失效率的先验分布为截尾Gamma分布时，给出了失效率的多层Bayes估计。在引进失效信息后，在失效率的先验分布为截尾Gamma分布时，给出了失效率的多层Bayes估计和综合估计，并给出了可靠度的综合估计，结合实际问题进行了计算。     

无失效数据失效概率的Bayes估计

本对无失效数据(t1,n1)在t1时刻的失效概串p1=p(T＜t1)的先验密度的校为(l--p1)2时,给出了p1的Bayes估计和多层Bayes估计,由此可以得到无失效数据可靠度的估计．最后,结合实际问题进行了计算．     

产品无失效数据的可靠性分析

本对某型发动机的无失效数据,给出了失效概率的多层Bayes估计,从而可以得到该型发动机可靠度的估计,并结合该型发动机的实际问题进行了计算。     

无失效数据的多层Bayes可靠性分析

本文对无失效数据（ti,ni）在时刻ti的失效概率pi＝p｛T＜ti｝的先验分布为不完全Beta分布时，给出了pi的多层Bayes估计，由此可以得到无失效数据可靠度的估计．     

E-Bayesian estimation of the reliability derived from Binomial distribution

This paper introduces a new parameter estimation method, named E-Bayesian estimation method, to estimate reliability derived from Binomial distribution. The definition of E-Bayesian estimation of the reliability is proposed, the formulas of E-Bayesian estimation and hierarchical Bayesian estimation of the reliability are also provided. Finally, it is shown, through a numerical example, that the new method is much simpler than hierarchical Bayesian estimation in practice.     

可靠度的E-Bayes估计、性质及应用

对二项分布的可靠度,提出了一种新的参数估计方法——E-Bayes估计法.在不同先验分布下,给出可靠度的E-Bayes估计和多层Bayes估计,并给出可靠度的E-Bayes估计的性质——E-Bayes估计和多层Bayes估计的关系.最后,给出了模拟算例,结果表明本文提出的方法可行且便于应用.     

A simulation based approach to the parameter estimation for the three-parameter gamma distribution

The gamma distribution is one of the commonly used statistical distribution in reliability. While maximum likelihood has traditionally been the main method for estimation of gamma parameters, Hirose has proposed a continuation method to parameter estimation for the three-parameter gamma distribution. In this paper, we propose to apply Markov chain Monte Carlo techniques to carry out a Bayesian estimation procedure using Hirose’s simulated data as well as two real data sets. The method is indeed flexible and inference for any quantity of interest is readily available.     

Reliability analysis for Weibull distribution with homogeneous heavily censored data based on Bayesian and least-squares methods

The reliability for Weibull distribution with homogeneous heavily censored data is analyzed in this study. The universal model of heavily censored data and existing methods, including maximum likelihood, least-squares, E-Bayesian estimation, and hierarchical Bayesian methods, are introduced. An improved method is proposed based on Bayesian inference and least-squares method. In this method, the Bayes estimations of failure probabilities are focused on for all the samples. The conjugate prior distribution of failure probability is set, and an optimization model is developed by maximizing the information entropy of prior distribution to determine the hyper-parameters. By integrating the likelihood function, the posterior distribution of failure probability is then derived to yield the Bayes estimation of failure probability. The estimations of reliability parameters are obtained by fitting distribution curve using least-squares method. The four existing methods are compared with the proposed method in terms of applicability, precision, efficiency, robustness, and simplicity. Specifically, the closed form expressions concerning E-Bayesian estimation and hierarchical Bayesian methods are derived and used. The comparisons demonstrate that the improved method is superior. Finally, three illustrative examples are presented to show the application of the proposed method.     

A Fuzzy Principal Component Analysis Approach to Hierarchical Evaluation Model for Balanced Supply Chain Scorecard Grading

Effective performance management is critical to efficient supply chain management systems with the balanced scorecard as well as to effective evaluation models and their algorithms. Problems often encountered in the modeling of the balanced scorecard for supply chain are how to overcome the multicollinearity in its index system. In this paper, a new fuzzy hierarchical evaluation model featuring the criteria of the balanced supply chain scorecard is proposed and analyzed on the basis of data about Chinese firms. The model, based on the fuzzy weight’s matrix derived from a fuzzy principal component analysis, overcomes the multicollinearity in the index system of the balanced supply chain scorecard. This method proves good performance in determining the weight distribution matrix of the fuzzy hierarchical evaluation and improves the evaluation accuracy and generalization as shown for a group of firms in western China.     

基于贝叶斯网络的供应链风险模糊综合评判

由于导致供应链失效的风险因素具有模糊性、复杂性,增加了供应链风险分析难度,一般的风险分析方法不能很好地评判供应链风险.文章提出了基于贝叶斯网络的供应链风险模糊综合评判方法,以某企业供应链风险为例,通过构建供应链失效风险的贝叶斯网络对风险事件发生概率进行线性推理,再采用模糊综合评判方法求出供应链风险中主要风险事件及总风险事件的风险等级,为该企业及早调控供应链提供依据.本评判方法可为企业供应链风险及其他类似风险的预防和控制提供参考依据.     

产品可靠度的E-Bayes估计

提出了参数估计的一种新方法——E-Bayes估计法.对Pascal分布,给出了可靠度的E-Bayes估计的定义(在先验分布中有一个超参数情形),在此基础上给出了可靠度的E-Bayes估计,并给出了可靠度的E-Bayes估计性质——E-Bayes估计和多层Bayes估计的关系.最后,给出了模拟算例,结果表明本文提出的E-Bayes估计法可行且便于工程应用.     

参数的E Bayes估计法及其应用

提出了参数的一种估计方法—— E Bayes估计法 ,对寿命服从指数分布的产品 ,在失效率的先验分布为 Gamma分布时 ,给出了失效率的 E Bayes估计和多层 Bayes估计 ,并在此基础上给出了失效率和可靠度的 E Bayes估计的性质 .结合实际问题进行了计算 ,结果表明提出的 E Bayes估计法可行且便于应用 .