A continuous-time semi-markov bayesian belief network model for availability measure estimation of fault tolerant systems

Detalhes bibliográficos
Autor(a) principal: Moura,Márcio das Chagas
Data de Publicação: 2008
Outros Autores: Droguett,Enrique López
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Pesquisa operacional (Online)
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0101-74382008000200011
Resumo: In this work it is proposed a model for the assessment of availability measure of fault tolerant systems based on the integration of continuous time semi-Markov processes and Bayesian belief networks. This integration results in a hybrid stochastic model that is able to represent the dynamic characteristics of a system as well as to deal with cause-effect relationships among external factors such as environmental and operational conditions. The hybrid model also allows for uncertainty propagation on the system availability. It is also proposed a numerical procedure for the solution of the state probability equations of semi-Markov processes described in terms of transition rates. The numerical procedure is based on the application of Laplace transforms that are inverted by the Gauss quadrature method known as Gauss Legendre. The hybrid model and numerical procedure are illustrated by means of an example of application in the context of fault tolerant systems.
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spelling A continuous-time semi-markov bayesian belief network model for availability measure estimation of fault tolerant systemssemi-Markov processesBayesian belief networksLaplace transformsavailability measurefault tolerant systemsIn this work it is proposed a model for the assessment of availability measure of fault tolerant systems based on the integration of continuous time semi-Markov processes and Bayesian belief networks. This integration results in a hybrid stochastic model that is able to represent the dynamic characteristics of a system as well as to deal with cause-effect relationships among external factors such as environmental and operational conditions. The hybrid model also allows for uncertainty propagation on the system availability. It is also proposed a numerical procedure for the solution of the state probability equations of semi-Markov processes described in terms of transition rates. The numerical procedure is based on the application of Laplace transforms that are inverted by the Gauss quadrature method known as Gauss Legendre. The hybrid model and numerical procedure are illustrated by means of an example of application in the context of fault tolerant systems.Sociedade Brasileira de Pesquisa Operacional2008-08-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0101-74382008000200011Pesquisa Operacional v.28 n.2 2008reponame:Pesquisa operacional (Online)instname:Sociedade Brasileira de Pesquisa Operacional (SOBRAPO)instacron:SOBRAPO10.1590/S0101-74382008000200011info:eu-repo/semantics/openAccessMoura,Márcio das ChagasDroguett,Enrique Lópezeng2008-10-20T00:00:00Zoai:scielo:S0101-74382008000200011Revistahttp://www.scielo.br/popehttps://old.scielo.br/oai/scielo-oai.php||sobrapo@sobrapo.org.br1678-51420101-7438opendoar:2008-10-20T00:00Pesquisa operacional (Online) - Sociedade Brasileira de Pesquisa Operacional (SOBRAPO)false
dc.title.none.fl_str_mv A continuous-time semi-markov bayesian belief network model for availability measure estimation of fault tolerant systems
title A continuous-time semi-markov bayesian belief network model for availability measure estimation of fault tolerant systems
spellingShingle A continuous-time semi-markov bayesian belief network model for availability measure estimation of fault tolerant systems
Moura,Márcio das Chagas
semi-Markov processes
Bayesian belief networks
Laplace transforms
availability measure
fault tolerant systems
title_short A continuous-time semi-markov bayesian belief network model for availability measure estimation of fault tolerant systems
title_full A continuous-time semi-markov bayesian belief network model for availability measure estimation of fault tolerant systems
title_fullStr A continuous-time semi-markov bayesian belief network model for availability measure estimation of fault tolerant systems
title_full_unstemmed A continuous-time semi-markov bayesian belief network model for availability measure estimation of fault tolerant systems
title_sort A continuous-time semi-markov bayesian belief network model for availability measure estimation of fault tolerant systems
author Moura,Márcio das Chagas
author_facet Moura,Márcio das Chagas
Droguett,Enrique López
author_role author
author2 Droguett,Enrique López
author2_role author
dc.contributor.author.fl_str_mv Moura,Márcio das Chagas
Droguett,Enrique López
dc.subject.por.fl_str_mv semi-Markov processes
Bayesian belief networks
Laplace transforms
availability measure
fault tolerant systems
topic semi-Markov processes
Bayesian belief networks
Laplace transforms
availability measure
fault tolerant systems
description In this work it is proposed a model for the assessment of availability measure of fault tolerant systems based on the integration of continuous time semi-Markov processes and Bayesian belief networks. This integration results in a hybrid stochastic model that is able to represent the dynamic characteristics of a system as well as to deal with cause-effect relationships among external factors such as environmental and operational conditions. The hybrid model also allows for uncertainty propagation on the system availability. It is also proposed a numerical procedure for the solution of the state probability equations of semi-Markov processes described in terms of transition rates. The numerical procedure is based on the application of Laplace transforms that are inverted by the Gauss quadrature method known as Gauss Legendre. The hybrid model and numerical procedure are illustrated by means of an example of application in the context of fault tolerant systems.
publishDate 2008
dc.date.none.fl_str_mv 2008-08-01
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0101-74382008000200011
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0101-74382008000200011
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1590/S0101-74382008000200011
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv text/html
dc.publisher.none.fl_str_mv Sociedade Brasileira de Pesquisa Operacional
publisher.none.fl_str_mv Sociedade Brasileira de Pesquisa Operacional
dc.source.none.fl_str_mv Pesquisa Operacional v.28 n.2 2008
reponame:Pesquisa operacional (Online)
instname:Sociedade Brasileira de Pesquisa Operacional (SOBRAPO)
instacron:SOBRAPO
instname_str Sociedade Brasileira de Pesquisa Operacional (SOBRAPO)
instacron_str SOBRAPO
institution SOBRAPO
reponame_str Pesquisa operacional (Online)
collection Pesquisa operacional (Online)
repository.name.fl_str_mv Pesquisa operacional (Online) - Sociedade Brasileira de Pesquisa Operacional (SOBRAPO)
repository.mail.fl_str_mv ||sobrapo@sobrapo.org.br
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