False-alarm and non-detection probabilities for on-line quality control via HMM
Autor(a) principal: | |
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Data de Publicação: | 2012 |
Outros Autores: | , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UFRN |
Texto Completo: | https://repositorio.ufrn.br/handle/123456789/50046 |
Resumo: | On-line quality control during production calls for monitoring produced items according to some prescribed strategy. It is reasonable to assume the existence of system internal non-observable variables so that the carried out monitoring is only partially reliable. In this note, under the setting of a Hidden Markov Model (HMM) and assuming that the evolution of the internal state changes are governed by a two-state Markov chain, we derive estimates for false-alarm and non-detection malfunctioning probabilities. Kernel density methods are used to approximate the stable regime density and the stationary probabilities. As a side result, alternative monitoring strategies are proposed. |
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Dorea, C.C.Y.Gonçalves, C.R.Medeiros, P.G.Santos, W.B.2022-12-08T20:18:22Z2022-12-08T20:18:22Z2012DOREA, C. C. Y.; et al. False-Alarm and non-detection probabilities for on-line quality control via HMM. International Journal of mathematical analysis, v. 6, p. 1153-1162, 2012. Disponível em: http://www.m-hikari.com/ijma/ijma-2012/ijma-21-24-2012/doreaIJMA21-24-2012.pdf . Acesso em: 11 dez. 20171312-8876https://repositorio.ufrn.br/handle/123456789/50046International Journal of Mathematical AnalysisHidden Markov modelFalse-alarmKernel density methodsFalse-alarm and non-detection probabilities for on-line quality control via HMMinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleOn-line quality control during production calls for monitoring produced items according to some prescribed strategy. It is reasonable to assume the existence of system internal non-observable variables so that the carried out monitoring is only partially reliable. In this note, under the setting of a Hidden Markov Model (HMM) and assuming that the evolution of the internal state changes are governed by a two-state Markov chain, we derive estimates for false-alarm and non-detection malfunctioning probabilities. Kernel density methods are used to approximate the stable regime density and the stationary probabilities. As a side result, alternative monitoring strategies are proposed.info:eu-repo/semantics/openAccessengreponame:Repositório Institucional da UFRNinstname:Universidade Federal do Rio Grande do Norte (UFRN)instacron:UFRNORIGINALFalse-Alarm_2012.pdfFalse-Alarm_2012.pdfapplication/pdf99221https://repositorio.ufrn.br/bitstream/123456789/50046/1/False-Alarm_2012.pdfe8de608f3222d80981f122b43c2a6f15MD51LICENSElicense.txtlicense.txttext/plain; charset=utf-81748https://repositorio.ufrn.br/bitstream/123456789/50046/2/license.txt8a4605be74aa9ea9d79846c1fba20a33MD52123456789/500462022-12-08 17:18:23.1oai:https://repositorio.ufrn.br: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Repositório de PublicaçõesPUBhttp://repositorio.ufrn.br/oai/opendoar:2022-12-08T20:18:23Repositório Institucional da UFRN - Universidade Federal do Rio Grande do Norte (UFRN)false |
dc.title.pt_BR.fl_str_mv |
False-alarm and non-detection probabilities for on-line quality control via HMM |
title |
False-alarm and non-detection probabilities for on-line quality control via HMM |
spellingShingle |
False-alarm and non-detection probabilities for on-line quality control via HMM Dorea, C.C.Y. Hidden Markov model False-alarm Kernel density methods |
title_short |
False-alarm and non-detection probabilities for on-line quality control via HMM |
title_full |
False-alarm and non-detection probabilities for on-line quality control via HMM |
title_fullStr |
False-alarm and non-detection probabilities for on-line quality control via HMM |
title_full_unstemmed |
False-alarm and non-detection probabilities for on-line quality control via HMM |
title_sort |
False-alarm and non-detection probabilities for on-line quality control via HMM |
author |
Dorea, C.C.Y. |
author_facet |
Dorea, C.C.Y. Gonçalves, C.R. Medeiros, P.G. Santos, W.B. |
author_role |
author |
author2 |
Gonçalves, C.R. Medeiros, P.G. Santos, W.B. |
author2_role |
author author author |
dc.contributor.author.fl_str_mv |
Dorea, C.C.Y. Gonçalves, C.R. Medeiros, P.G. Santos, W.B. |
dc.subject.por.fl_str_mv |
Hidden Markov model False-alarm Kernel density methods |
topic |
Hidden Markov model False-alarm Kernel density methods |
description |
On-line quality control during production calls for monitoring produced items according to some prescribed strategy. It is reasonable to assume the existence of system internal non-observable variables so that the carried out monitoring is only partially reliable. In this note, under the setting of a Hidden Markov Model (HMM) and assuming that the evolution of the internal state changes are governed by a two-state Markov chain, we derive estimates for false-alarm and non-detection malfunctioning probabilities. Kernel density methods are used to approximate the stable regime density and the stationary probabilities. As a side result, alternative monitoring strategies are proposed. |
publishDate |
2012 |
dc.date.issued.fl_str_mv |
2012 |
dc.date.accessioned.fl_str_mv |
2022-12-08T20:18:22Z |
dc.date.available.fl_str_mv |
2022-12-08T20:18:22Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.citation.fl_str_mv |
DOREA, C. C. Y.; et al. False-Alarm and non-detection probabilities for on-line quality control via HMM. International Journal of mathematical analysis, v. 6, p. 1153-1162, 2012. Disponível em: http://www.m-hikari.com/ijma/ijma-2012/ijma-21-24-2012/doreaIJMA21-24-2012.pdf . Acesso em: 11 dez. 2017 |
dc.identifier.uri.fl_str_mv |
https://repositorio.ufrn.br/handle/123456789/50046 |
dc.identifier.issn.none.fl_str_mv |
1312-8876 |
identifier_str_mv |
DOREA, C. C. Y.; et al. False-Alarm and non-detection probabilities for on-line quality control via HMM. International Journal of mathematical analysis, v. 6, p. 1153-1162, 2012. Disponível em: http://www.m-hikari.com/ijma/ijma-2012/ijma-21-24-2012/doreaIJMA21-24-2012.pdf . Acesso em: 11 dez. 2017 1312-8876 |
url |
https://repositorio.ufrn.br/handle/123456789/50046 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.publisher.none.fl_str_mv |
International Journal of Mathematical Analysis |
publisher.none.fl_str_mv |
International Journal of Mathematical Analysis |
dc.source.none.fl_str_mv |
reponame:Repositório Institucional da UFRN instname:Universidade Federal do Rio Grande do Norte (UFRN) instacron:UFRN |
instname_str |
Universidade Federal do Rio Grande do Norte (UFRN) |
instacron_str |
UFRN |
institution |
UFRN |
reponame_str |
Repositório Institucional da UFRN |
collection |
Repositório Institucional da UFRN |
bitstream.url.fl_str_mv |
https://repositorio.ufrn.br/bitstream/123456789/50046/1/False-Alarm_2012.pdf https://repositorio.ufrn.br/bitstream/123456789/50046/2/license.txt |
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Repositório Institucional da UFRN - Universidade Federal do Rio Grande do Norte (UFRN) |
repository.mail.fl_str_mv |
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1802117551263580160 |