SCAT Model Based on Bayesian Networks for Lost-Time Accident Prevention and Rate Reduction in Peruvian Mining Operations

Descripción del Articulo

El texto completo de este trabajo no está disponible en el Repositorio Académico UPC por restricciones de la casa editorial donde ha sido publicado.
Detalles Bibliográficos
Autores: Ziegler-Barranco, Ana, Mera-Barco, Luis, Aramburu-Rojas, Vidal, Raymundo, Carlos, Mamani-Macedo, Nestor, Dominguez, Francisco
Formato: artículo
Fecha de Publicación:2020
Institución:Universidad Peruana de Ciencias Aplicadas
Repositorio:UPC-Institucional
Lenguaje:inglés
OAI Identifier:oai:repositorioacademico.upc.edu.pe:10757/656168
Enlace del recurso:http://hdl.handle.net/10757/656168
Nivel de acceso:acceso embargado
Materia:Accident
Bayesian net-work
Mining
Peruvian
Prevention
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network_acronym_str UUPC
network_name_str UPC-Institucional
repository_id_str 2670
dc.title.en_US.fl_str_mv SCAT Model Based on Bayesian Networks for Lost-Time Accident Prevention and Rate Reduction in Peruvian Mining Operations
title SCAT Model Based on Bayesian Networks for Lost-Time Accident Prevention and Rate Reduction in Peruvian Mining Operations
spellingShingle SCAT Model Based on Bayesian Networks for Lost-Time Accident Prevention and Rate Reduction in Peruvian Mining Operations
Ziegler-Barranco, Ana
Accident
Bayesian net-work
Mining
Peruvian
Prevention
title_short SCAT Model Based on Bayesian Networks for Lost-Time Accident Prevention and Rate Reduction in Peruvian Mining Operations
title_full SCAT Model Based on Bayesian Networks for Lost-Time Accident Prevention and Rate Reduction in Peruvian Mining Operations
title_fullStr SCAT Model Based on Bayesian Networks for Lost-Time Accident Prevention and Rate Reduction in Peruvian Mining Operations
title_full_unstemmed SCAT Model Based on Bayesian Networks for Lost-Time Accident Prevention and Rate Reduction in Peruvian Mining Operations
title_sort SCAT Model Based on Bayesian Networks for Lost-Time Accident Prevention and Rate Reduction in Peruvian Mining Operations
author Ziegler-Barranco, Ana
author_facet Ziegler-Barranco, Ana
Mera-Barco, Luis
Aramburu-Rojas, Vidal
Raymundo, Carlos
Mamani-Macedo, Nestor
Dominguez, Francisco
author_role author
author2 Mera-Barco, Luis
Aramburu-Rojas, Vidal
Raymundo, Carlos
Mamani-Macedo, Nestor
Dominguez, Francisco
author2_role author
author
author
author
author
dc.contributor.author.fl_str_mv Ziegler-Barranco, Ana
Mera-Barco, Luis
Aramburu-Rojas, Vidal
Raymundo, Carlos
Mamani-Macedo, Nestor
Dominguez, Francisco
dc.subject.en_US.fl_str_mv Accident
Bayesian net-work
Mining
Peruvian
Prevention
topic Accident
Bayesian net-work
Mining
Peruvian
Prevention
description El texto completo de este trabajo no está disponible en el Repositorio Académico UPC por restricciones de la casa editorial donde ha sido publicado.
publishDate 2020
dc.date.accessioned.none.fl_str_mv 2021-05-27T12:30:06Z
dc.date.available.none.fl_str_mv 2021-05-27T12:30:06Z
dc.date.issued.fl_str_mv 2020-01-01
dc.type.en_US.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.issn.none.fl_str_mv 21945357
dc.identifier.doi.none.fl_str_mv 10.1007/978-3-030-50791-6_45
dc.identifier.uri.none.fl_str_mv http://hdl.handle.net/10757/656168
dc.identifier.eissn.none.fl_str_mv 21945365
dc.identifier.journal.en_US.fl_str_mv Advances in Intelligent Systems and Computing
dc.identifier.eid.none.fl_str_mv 2-s2.0-85088231547
dc.identifier.scopusid.none.fl_str_mv SCOPUS_ID:85088231547
dc.identifier.isni.none.fl_str_mv 0000 0001 2196 144X
identifier_str_mv 21945357
10.1007/978-3-030-50791-6_45
21945365
Advances in Intelligent Systems and Computing
2-s2.0-85088231547
SCOPUS_ID:85088231547
0000 0001 2196 144X
url http://hdl.handle.net/10757/656168
dc.language.iso.en_US.fl_str_mv eng
language eng
dc.relation.url.en_US.fl_str_mv https://www.springerprofessional.de/en/scat-model-based-on-bayesian-networks-for-lost-time-accident-pre/18134120
dc.rights.en_US.fl_str_mv info:eu-repo/semantics/embargoedAccess
eu_rights_str_mv embargoedAccess
dc.format.en_US.fl_str_mv application/html
dc.publisher.en_US.fl_str_mv Springer
dc.source.es_PE.fl_str_mv Universidad Peruana de Ciencias Aplicadas (UPC)
Repositorio Académico - UPC
dc.source.none.fl_str_mv reponame:UPC-Institucional
instname:Universidad Peruana de Ciencias Aplicadas
instacron:UPC
instname_str Universidad Peruana de Ciencias Aplicadas
instacron_str UPC
institution UPC
reponame_str UPC-Institucional
collection UPC-Institucional
dc.source.journaltitle.none.fl_str_mv Advances in Intelligent Systems and Computing
dc.source.volume.none.fl_str_mv 1209 AISC
dc.source.beginpage.none.fl_str_mv 350
dc.source.endpage.none.fl_str_mv 358
bitstream.url.fl_str_mv https://repositorioacademico.upc.edu.pe/bitstream/10757/656168/1/license.txt
bitstream.checksum.fl_str_mv 8a4605be74aa9ea9d79846c1fba20a33
bitstream.checksumAlgorithm.fl_str_mv MD5
repository.name.fl_str_mv Repositorio académico upc
repository.mail.fl_str_mv upc@openrepository.com
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spelling fe5bfc614d0cde0e840b0f1649575a9d30053b620bf5c5c39f3d0db1c808b09eaf63003c2c18274ebf15d91ddeec580cbec89df1b29165990ab4ce165cbf28f5e4ccd95003c4929de31ab03204ce4b92da8cfadf8500bca061da163b707885b99dc247d3d44a500Ziegler-Barranco, AnaMera-Barco, LuisAramburu-Rojas, VidalRaymundo, CarlosMamani-Macedo, NestorDominguez, Francisco2021-05-27T12:30:06Z2021-05-27T12:30:06Z2020-01-012194535710.1007/978-3-030-50791-6_45http://hdl.handle.net/10757/65616821945365Advances in Intelligent Systems and Computing2-s2.0-85088231547SCOPUS_ID:850882315470000 0001 2196 144XEl texto completo de este trabajo no está disponible en el Repositorio Académico UPC por restricciones de la casa editorial donde ha sido publicado.Several factors affect the activities of the mining industry. For example, accident rates are critical because they affect company ratings in the stock market (Standard & Poors). Considering that the corporate image is directly related to its stakeholders, this study conducts an accident analysis using quantitative and qualitative methods. In this way, the contingency rate is controlled, mitigated, and prevented while serving the needs) of the stakeholders. The Bayesian network method contributes to decision-making through a set of variables and the dependency relationships between them, establishing an earlier probability of unknown variables. Bayesian models have different applications, such as diagnosis, classification, and decision, and establish relationships among variables and cause–effect links. This study uses Bayesian inference to identify the various patterns that influence operator accident rates at a contractor mining company, and therefore, study and assess the possible differences in its future operations.application/htmlengSpringerhttps://www.springerprofessional.de/en/scat-model-based-on-bayesian-networks-for-lost-time-accident-pre/18134120info:eu-repo/semantics/embargoedAccessUniversidad Peruana de Ciencias Aplicadas (UPC)Repositorio Académico - UPCAdvances in Intelligent Systems and Computing1209 AISC350358reponame:UPC-Institucionalinstname:Universidad Peruana de Ciencias Aplicadasinstacron:UPCAccidentBayesian net-workMiningPeruvianPreventionSCAT Model Based on Bayesian Networks for Lost-Time Accident Prevention and Rate Reduction in Peruvian Mining Operationsinfo:eu-repo/semantics/articleLICENSElicense.txtlicense.txttext/plain; charset=utf-81748https://repositorioacademico.upc.edu.pe/bitstream/10757/656168/1/license.txt8a4605be74aa9ea9d79846c1fba20a33MD51false10757/656168oai:repositorioacademico.upc.edu.pe:10757/6561682021-05-27 12:30:06.823Repositorio académico upcupc@openrepository.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SCAT Model Based on Bayesian Networks for Lost-Time Accident Prevention and Rate Reduction in Peruvian Mining Operations
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