Markov chains for the identification of areas at higher risk of earthquake occurrence in Lima-Ica 2019

Descripción del Articulo

In this study, the Markov Chains model was applied to identify areas with the highest risk of earthquakes in the geographic area of Lima - Ica, which is considered one of the most active seismic zones in Peru. There are few research works with the application of probabilistic models to earthquakes i...

Descripción completa

Detalles Bibliográficos
Autor: Risco Franco, Carlos
Formato: artículo
Fecha de Publicación:2019
Institución:Universidad Nacional de Ingeniería
Repositorio:Revistas - Universidad Nacional de Ingeniería
Lenguaje:español
inglés
OAI Identifier:oai:oai:revistas.uni.edu.pe:article/1187
Enlace del recurso:https://revistas.uni.edu.pe/index.php/iecos/article/view/1187
Nivel de acceso:acceso abierto
Materia:Sismos
cadenas de Markov
CTIP
Earthquakes
Markov chains
id REVUNI_f9fec90756aa4ff37a91311c01fd83a6
oai_identifier_str oai:oai:revistas.uni.edu.pe:article/1187
network_acronym_str REVUNI
network_name_str Revistas - Universidad Nacional de Ingeniería
repository_id_str
spelling Markov chains for the identification of areas at higher risk of earthquake occurrence in Lima-Ica 2019Cadenas de Markov para la identificación de zonas de mayor riesgo de ocurrencia de sismos en Lima-Ica 2019Risco Franco, CarlosSismoscadenas de MarkovCTIPEarthquakesMarkov chainsCTIPIn this study, the Markov Chains model was applied to identify areas with the highest risk of earthquakes in the geographic area of Lima - Ica, which is considered one of the most active seismic zones in Peru. There are few research works with the application of probabilistic models to earthquakes in Peru. In the present study we have used the information of the earthquakes that have occurred in Lima-Ica from 2017 to 2019 (IGP) and we have found that the Lima-Oeste area is the one with the highest risk of earthquakes, approaching this result , for the case of Lima, with the result found by other authors, with different methods.En este estudio se aplicó el modelo de cadenas de Markov para identificar zonas de mayor riesgo de ocurrencia de sismos en el área geográfica de Lima-Ica, la cual es considerada una de las zonas sísmicas más activas del Perú. Existen pocos trabajos de investigación con aplicación de modelos probabilísticos a sismos en el Perú. En el presente estudio hemos usado la información de los sismos que han ocurrido en Lima- Ica del 2017 al 2019 (IGP) y hemos hallado que la zona de Lima-Oeste, es la que presenta mayor riesgo de ocurrencia de sismos, aproximándose este resultado, para el caso de Lima, con el resultado hallado por otros autores, con métodos diferentes.Universidad Nacional de Ingeniería2019-11-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionPeer ReviewedEvaluado por paresapplication/pdfaudio/mpegaudio/mpeghttps://revistas.uni.edu.pe/index.php/iecos/article/view/118710.21754/iecos.v20i0.1187revista IECOS; Vol. 20 (2019); 115-124Revista IECOS; Vol. 20 (2019); 115-1242788-74802961-284510.21754/iecos.v20i0reponame:Revistas - Universidad Nacional de Ingenieríainstname:Universidad Nacional de Ingenieríainstacron:UNIspaenghttps://revistas.uni.edu.pe/index.php/iecos/article/view/1187/3200https://revistas.uni.edu.pe/index.php/iecos/article/view/1187/3201https://revistas.uni.edu.pe/index.php/iecos/article/view/1187/3202Derechos de autor 2019 Carlos Risco Francohttps://creativecommons.org/licenses/by/4.0info:eu-repo/semantics/openAccessoai:oai:revistas.uni.edu.pe:article/11872025-01-20T10:12:44Z
dc.title.none.fl_str_mv Markov chains for the identification of areas at higher risk of earthquake occurrence in Lima-Ica 2019
Cadenas de Markov para la identificación de zonas de mayor riesgo de ocurrencia de sismos en Lima-Ica 2019
title Markov chains for the identification of areas at higher risk of earthquake occurrence in Lima-Ica 2019
spellingShingle Markov chains for the identification of areas at higher risk of earthquake occurrence in Lima-Ica 2019
Risco Franco, Carlos
Sismos
cadenas de Markov
CTIP
Earthquakes
Markov chains
CTIP
title_short Markov chains for the identification of areas at higher risk of earthquake occurrence in Lima-Ica 2019
title_full Markov chains for the identification of areas at higher risk of earthquake occurrence in Lima-Ica 2019
title_fullStr Markov chains for the identification of areas at higher risk of earthquake occurrence in Lima-Ica 2019
title_full_unstemmed Markov chains for the identification of areas at higher risk of earthquake occurrence in Lima-Ica 2019
title_sort Markov chains for the identification of areas at higher risk of earthquake occurrence in Lima-Ica 2019
dc.creator.none.fl_str_mv Risco Franco, Carlos
author Risco Franco, Carlos
author_facet Risco Franco, Carlos
author_role author
dc.subject.none.fl_str_mv Sismos
cadenas de Markov
CTIP
Earthquakes
Markov chains
CTIP
topic Sismos
cadenas de Markov
CTIP
Earthquakes
Markov chains
CTIP
description In this study, the Markov Chains model was applied to identify areas with the highest risk of earthquakes in the geographic area of Lima - Ica, which is considered one of the most active seismic zones in Peru. There are few research works with the application of probabilistic models to earthquakes in Peru. In the present study we have used the information of the earthquakes that have occurred in Lima-Ica from 2017 to 2019 (IGP) and we have found that the Lima-Oeste area is the one with the highest risk of earthquakes, approaching this result , for the case of Lima, with the result found by other authors, with different methods.
publishDate 2019
dc.date.none.fl_str_mv 2019-11-01
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Peer Reviewed
Evaluado por pares
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv https://revistas.uni.edu.pe/index.php/iecos/article/view/1187
10.21754/iecos.v20i0.1187
url https://revistas.uni.edu.pe/index.php/iecos/article/view/1187
identifier_str_mv 10.21754/iecos.v20i0.1187
dc.language.none.fl_str_mv spa
eng
language spa
eng
dc.relation.none.fl_str_mv https://revistas.uni.edu.pe/index.php/iecos/article/view/1187/3200
https://revistas.uni.edu.pe/index.php/iecos/article/view/1187/3201
https://revistas.uni.edu.pe/index.php/iecos/article/view/1187/3202
dc.rights.none.fl_str_mv Derechos de autor 2019 Carlos Risco Franco
https://creativecommons.org/licenses/by/4.0
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Derechos de autor 2019 Carlos Risco Franco
https://creativecommons.org/licenses/by/4.0
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
audio/mpeg
audio/mpeg
dc.publisher.none.fl_str_mv Universidad Nacional de Ingeniería
publisher.none.fl_str_mv Universidad Nacional de Ingeniería
dc.source.none.fl_str_mv revista IECOS; Vol. 20 (2019); 115-124
Revista IECOS; Vol. 20 (2019); 115-124
2788-7480
2961-2845
10.21754/iecos.v20i0
reponame:Revistas - Universidad Nacional de Ingeniería
instname:Universidad Nacional de Ingeniería
instacron:UNI
instname_str Universidad Nacional de Ingeniería
instacron_str UNI
institution UNI
reponame_str Revistas - Universidad Nacional de Ingeniería
collection Revistas - Universidad Nacional de Ingeniería
repository.name.fl_str_mv
repository.mail.fl_str_mv
_version_ 1833562789465030656
score 13.924177
Nota importante:
La información contenida en este registro es de entera responsabilidad de la institución que gestiona el repositorio institucional donde esta contenido este documento o set de datos. El CONCYTEC no se hace responsable por los contenidos (publicaciones y/o datos) accesibles a través del Repositorio Nacional Digital de Ciencia, Tecnología e Innovación de Acceso Abierto (ALICIA).