Estimation of waste‐to‐energy system reliability under hierarchical Bayesian
In this paper, we discuss about the hierarchical Bayesian (HB) estimation concerning system reliability for a waste‐to‐energy (WTE) process. The main goal of this approach is to obtain this estimation WTE process reliability under different loss functions related series, parallel, and k‐out‐of‐m sys...
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Veröffentlicht in: | Quality and reliability engineering international 2022-11, Vol.38 (7), p.3892-3918 |
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description | In this paper, we discuss about the hierarchical Bayesian (HB) estimation concerning system reliability for a waste‐to‐energy (WTE) process. The main goal of this approach is to obtain this estimation WTE process reliability under different loss functions related series, parallel, and k‐out‐of‐m systems. In this case, we can drive system outcome by estimating each individual component. It is assumed that components are independent and identically distributed exponential random variables. Properties of the HB estimations under different loss functions are also provided, and comparisons are made between Bayesian and HB estimators via Monte Carlo simulation. The implementation of the proposed procedure was illustrated in detail by employing numerical practical examples extracted from a WTE process at the final part of this paper. |
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M.</creatorcontrib><creatorcontrib>Fazlollahtabar, Hamed</creatorcontrib><title>Estimation of waste‐to‐energy system reliability under hierarchical Bayesian</title><title>Quality and reliability engineering international</title><description>In this paper, we discuss about the hierarchical Bayesian (HB) estimation concerning system reliability for a waste‐to‐energy (WTE) process. The main goal of this approach is to obtain this estimation WTE process reliability under different loss functions related series, parallel, and k‐out‐of‐m systems. In this case, we can drive system outcome by estimating each individual component. It is assumed that components are independent and identically distributed exponential random variables. Properties of the HB estimations under different loss functions are also provided, and comparisons are made between Bayesian and HB estimators via Monte Carlo simulation. The implementation of the proposed procedure was illustrated in detail by employing numerical practical examples extracted from a WTE process at the final part of this paper.</description><subject>Bayesian analysis</subject><subject>Estimation</subject><subject>hierarchical Bayesian</subject><subject>Mellin transform</subject><subject>Random variables</subject><subject>System reliability</subject><issn>0748-8017</issn><issn>1099-1638</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><recordid>eNp10M1KAzEQB_AgCtYq-AgBL1625qPbZI9a6gcIfqDnMJud2JTtbptsKXvzEXxGn8TUevUyA8OPGeZPyDlnI86YuFoHHEmu5QEZcFYUGZ9IfUgGTI11phlXx-QkxgVjCRd6QJ5nsfNL6Hzb0NbRLcQOvz-_ujYVbDB89DT2abakAWsPpa9919NNU2Ggc48Bgp17CzW9gR6jh-aUHDmoI5799SF5v529Te-zx6e7h-n1Y2YFVzJzE1DINQjpKiaFsACoSp0r5YQociiUBYGiKHmOEsZ5zh3LpdVWsKpSJZNDcrHfuwrteoOxM4t2E5p00gglJBtLJUVSl3tlQxtjQGdWIb0besOZ2eVlUl5ml1ei2Z5ufY39v868vM5-_Q_nJm5s</recordid><startdate>202211</startdate><enddate>202211</enddate><creator>Gholizadeh, Ramin</creator><creator>londono, Sergio L. 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subjects | Bayesian analysis Estimation hierarchical Bayesian Mellin transform Random variables System reliability |
title | Estimation of waste‐to‐energy system reliability under hierarchical Bayesian |
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