ARIMA models for the analysis of earthquake data in Peru in 2017
Descripción del Articulo
This project seeks to explore the phenomenon of earthquakes through the use of statistical tools, in this case to characterize and search for patterns of behavior of earthquakes, which have occurred in Peru in 2017; for this purpose, techniques such as Cluster Analysis and Time Series Models are use...
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Formato: | artículo |
Fecha de Publicación: | 2017 |
Institución: | Universidad Nacional de Ingeniería |
Repositorio: | Revistas - Universidad Nacional de Ingeniería |
Lenguaje: | español inglés |
OAI Identifier: | oai:oai:revistas.uni.edu.pe:article/1179 |
Enlace del recurso: | https://revistas.uni.edu.pe/index.php/iecos/article/view/1179 |
Nivel de acceso: | acceso abierto |
Materia: | Modelos de Series de tiempo ARIMA Cluster Analysis sismo Time Series Models ARIMA Cluster Analysis Earthquake |
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ARIMA models for the analysis of earthquake data in Peru in 2017Modelos ARIMA para el análisis de datos de sismos en el Perú en 2017Risco Franco, CarlosModelos de Series de tiempo ARIMACluster AnalysissismoTime Series ModelsARIMA Cluster AnalysisEarthquakeThis project seeks to explore the phenomenon of earthquakes through the use of statistical tools, in this case to characterize and search for patterns of behavior of earthquakes, which have occurred in Peru in 2017; for this purpose, techniques such as Cluster Analysis and Time Series Models are used. First, the zones of greatest seismic activity have been identified and then their main characteristics have been found, as well as the interrelation between magnitude and depth. Apart from identifying the seismic zones, a small decreasing trend in the magnitude of earthquakes in Lima in the last three months has been observed. The data have been fitted to an ARIMA (1,1,0) time series model, which has been found to be significant, both at the national level and for Lima-Ica and Arequipa. Data from the Peruvian Geophysical Institute on its web page has been used. The most active area is the Arequipa area, followed by Lima.Este proyecto busca explorar el fenómeno de los sismos mediante el uso de herramientas estadísticas, en este caso para caracterizar y buscar patrones de comportamiento de los mismos, que se han presentado en el Perú en el 2017; para ello se usan técnicas como el Cluster Análysis y Modelos de Series de Tiempo. Primero se ha identificado las zonas de mayor actividad sísmica y luego se ha hallado sus características principales, así como la interrelación entre magnitud y profundidad. Aparte de identificar las zonas sísmicas, se observa una pequeña tendencia a la disminución en la magnitud de los sismos en Lima en los últimos tres meses. Los datos se han ajustado a un modelo de series de tiempo ARIMA (1,1,0), el cual ha resultado significativo, tanto a nivel nacional, como para Lima-Ica y Arequipa. Se ha utilizado datos del Instituto Geofísico del Perú en su página web. La zona de mayor actividad es la zona de Arequipa, seguida de la de Lima.Universidad Nacional de Ingeniería2017-07-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionPeer ReviewedEvaluado por paresapplication/pdfaudio/mpegaudio/mpeghttps://revistas.uni.edu.pe/index.php/iecos/article/view/117910.21754/iecos.v18i0.1179revista IECOS; Vol. 18 (2017); 143-157Revista IECOS; Vol. 18 (2017); 143-1572788-74802961-284510.21754/iecos.v18i0reponame:Revistas - Universidad Nacional de Ingenieríainstname:Universidad Nacional de Ingenieríainstacron:UNIspaenghttps://revistas.uni.edu.pe/index.php/iecos/article/view/1179/3151https://revistas.uni.edu.pe/index.php/iecos/article/view/1179/3152https://revistas.uni.edu.pe/index.php/iecos/article/view/1179/3153Derechos de autor 2017 Carlos Risco Francohttps://creativecommons.org/licenses/by/4.0info:eu-repo/semantics/openAccessoai:oai:revistas.uni.edu.pe:article/11792025-01-20T02:54:13Z |
dc.title.none.fl_str_mv |
ARIMA models for the analysis of earthquake data in Peru in 2017 Modelos ARIMA para el análisis de datos de sismos en el Perú en 2017 |
title |
ARIMA models for the analysis of earthquake data in Peru in 2017 |
spellingShingle |
ARIMA models for the analysis of earthquake data in Peru in 2017 Risco Franco, Carlos Modelos de Series de tiempo ARIMA Cluster Analysis sismo Time Series Models ARIMA Cluster Analysis Earthquake |
title_short |
ARIMA models for the analysis of earthquake data in Peru in 2017 |
title_full |
ARIMA models for the analysis of earthquake data in Peru in 2017 |
title_fullStr |
ARIMA models for the analysis of earthquake data in Peru in 2017 |
title_full_unstemmed |
ARIMA models for the analysis of earthquake data in Peru in 2017 |
title_sort |
ARIMA models for the analysis of earthquake data in Peru in 2017 |
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 |
Modelos de Series de tiempo ARIMA Cluster Analysis sismo Time Series Models ARIMA Cluster Analysis Earthquake |
topic |
Modelos de Series de tiempo ARIMA Cluster Analysis sismo Time Series Models ARIMA Cluster Analysis Earthquake |
description |
This project seeks to explore the phenomenon of earthquakes through the use of statistical tools, in this case to characterize and search for patterns of behavior of earthquakes, which have occurred in Peru in 2017; for this purpose, techniques such as Cluster Analysis and Time Series Models are used. First, the zones of greatest seismic activity have been identified and then their main characteristics have been found, as well as the interrelation between magnitude and depth. Apart from identifying the seismic zones, a small decreasing trend in the magnitude of earthquakes in Lima in the last three months has been observed. The data have been fitted to an ARIMA (1,1,0) time series model, which has been found to be significant, both at the national level and for Lima-Ica and Arequipa. Data from the Peruvian Geophysical Institute on its web page has been used. The most active area is the Arequipa area, followed by Lima. |
publishDate |
2017 |
dc.date.none.fl_str_mv |
2017-07-01 |
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/1179 10.21754/iecos.v18i0.1179 |
url |
https://revistas.uni.edu.pe/index.php/iecos/article/view/1179 |
identifier_str_mv |
10.21754/iecos.v18i0.1179 |
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/1179/3151 https://revistas.uni.edu.pe/index.php/iecos/article/view/1179/3152 https://revistas.uni.edu.pe/index.php/iecos/article/view/1179/3153 |
dc.rights.none.fl_str_mv |
Derechos de autor 2017 Carlos Risco Franco https://creativecommons.org/licenses/by/4.0 info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
Derechos de autor 2017 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. 18 (2017); 143-157 Revista IECOS; Vol. 18 (2017); 143-157 2788-7480 2961-2845 10.21754/iecos.v18i0 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 |
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repository.mail.fl_str_mv |
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1833562789332910080 |
score |
13.940932 |
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).
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).