BAYESIAN STATISTICAL FUSION RELIABILITY EVALUATION MODEL OF MULTI-SOURCE HETEROGENEOUS DATA

In order to solve the reliability evaluation of small samples for the high reliability, long-life products and to improve the accuracy of reliability evaluation, the Bayesian reliability evaluation model of multiple information source data fusion was carried out. First, a set of data as the initial...

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Main Authors: TANG Li, TANG JiaYin, CHENG ShiJuan
Format: Article
Language:zho
Published: Editorial Office of Journal of Mechanical Strength 2022-01-01
Series:Jixie qiangdu
Subjects:
Online Access:http://www.jxqd.net.cn/thesisDetails#10.16579/j.issn.1001.9669.2022.01.017
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author TANG Li
TANG JiaYin
CHENG ShiJuan
author_facet TANG Li
TANG JiaYin
CHENG ShiJuan
author_sort TANG Li
collection DOAJ
description In order to solve the reliability evaluation of small samples for the high reliability, long-life products and to improve the accuracy of reliability evaluation, the Bayesian reliability evaluation model of multiple information source data fusion was carried out. First, a set of data as the initial prior information of another information source in this model was selected, by using the posterior density according to Bayesian estimation. Then, it as the prior distribution of the next information source was used. Through iteration, the joint posterior density and reliability index data of multi-source heterogeneous data are obtained, and the corresponding reliability analysis is completed. Finally, a simulation example verifies the rationality and effectiveness of the model.
format Article
id doaj-art-06952107f1d5408aa2b7d415ffda6490
institution Kabale University
issn 1001-9669
language zho
publishDate 2022-01-01
publisher Editorial Office of Journal of Mechanical Strength
record_format Article
series Jixie qiangdu
spelling doaj-art-06952107f1d5408aa2b7d415ffda64902025-01-15T02:24:49ZzhoEditorial Office of Journal of Mechanical StrengthJixie qiangdu1001-96692022-01-014412613229910279BAYESIAN STATISTICAL FUSION RELIABILITY EVALUATION MODEL OF MULTI-SOURCE HETEROGENEOUS DATATANG LiTANG JiaYinCHENG ShiJuanIn order to solve the reliability evaluation of small samples for the high reliability, long-life products and to improve the accuracy of reliability evaluation, the Bayesian reliability evaluation model of multiple information source data fusion was carried out. First, a set of data as the initial prior information of another information source in this model was selected, by using the posterior density according to Bayesian estimation. Then, it as the prior distribution of the next information source was used. Through iteration, the joint posterior density and reliability index data of multi-source heterogeneous data are obtained, and the corresponding reliability analysis is completed. Finally, a simulation example verifies the rationality and effectiveness of the model.http://www.jxqd.net.cn/thesisDetails#10.16579/j.issn.1001.9669.2022.01.017DataInformation fusionBayesian estimationReliability assessment
spellingShingle TANG Li
TANG JiaYin
CHENG ShiJuan
BAYESIAN STATISTICAL FUSION RELIABILITY EVALUATION MODEL OF MULTI-SOURCE HETEROGENEOUS DATA
Jixie qiangdu
Data
Information fusion
Bayesian estimation
Reliability assessment
title BAYESIAN STATISTICAL FUSION RELIABILITY EVALUATION MODEL OF MULTI-SOURCE HETEROGENEOUS DATA
title_full BAYESIAN STATISTICAL FUSION RELIABILITY EVALUATION MODEL OF MULTI-SOURCE HETEROGENEOUS DATA
title_fullStr BAYESIAN STATISTICAL FUSION RELIABILITY EVALUATION MODEL OF MULTI-SOURCE HETEROGENEOUS DATA
title_full_unstemmed BAYESIAN STATISTICAL FUSION RELIABILITY EVALUATION MODEL OF MULTI-SOURCE HETEROGENEOUS DATA
title_short BAYESIAN STATISTICAL FUSION RELIABILITY EVALUATION MODEL OF MULTI-SOURCE HETEROGENEOUS DATA
title_sort bayesian statistical fusion reliability evaluation model of multi source heterogeneous data
topic Data
Information fusion
Bayesian estimation
Reliability assessment
url http://www.jxqd.net.cn/thesisDetails#10.16579/j.issn.1001.9669.2022.01.017
work_keys_str_mv AT tangli bayesianstatisticalfusionreliabilityevaluationmodelofmultisourceheterogeneousdata
AT tangjiayin bayesianstatisticalfusionreliabilityevaluationmodelofmultisourceheterogeneousdata
AT chengshijuan bayesianstatisticalfusionreliabilityevaluationmodelofmultisourceheterogeneousdata