Time series analysis of earthquake data in Peru 2017-2018
Descripción del Articulo
The objective of this work is to characterize and look for behavior patterns, in areas with earthquake clusters, through the use of time series and the data of the earthquakes that occurred in Peru in 2017 and 2018.In this exploratory work, we have first used Cluster Analysis to form groups or geogr...
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Formato: | artículo |
Fecha de Publicación: | 2018 |
Institución: | Universidad Nacional de Ingeniería |
Repositorio: | Revistas - Universidad Nacional de Ingeniería |
Lenguaje: | español inglés |
OAI Identifier: | oai:oai:revistas.uni.edu.pe:article/1173 |
Enlace del recurso: | https://revistas.uni.edu.pe/index.php/iecos/article/view/1173 |
Nivel de acceso: | acceso abierto |
Materia: | sismos análisis de series de tiempo cluster analysis earthquakes time series analysis |
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Time series analysis of earthquake data in Peru 2017-2018Análisis de series de tiempo de datos de sismos en el Perú 2017-2018Risco Franco, Carlossismosanálisis de series de tiempocluster analysisearthquakestime series analysiscluster analysisThe objective of this work is to characterize and look for behavior patterns, in areas with earthquake clusters, through the use of time series and the data of the earthquakes that occurred in Peru in 2017 and 2018.In this exploratory work, we have first used Cluster Analysis to form groups or geographic areas with near earthquake occurrence. Then we have found that the magnitude of the earthquakes in time, evaluated by geographical proximity zones, would be correlated with the magnitude of the previous earthquake, hence it was appropriate to use the ARIMA model (1,1,0), in which It is considered a lag and a difference to eliminate the presence of some trend, without the presence of moving average. We have identified eight geographical areas, in which the earthquakes are grouped. Among other results we have found that in the Arequipa-Tacna and Lima-Ica areas, the magnitudes of the earthquakes in relation to the arrival time, conform to an ARIMA model (1,1,0). On the other hand, we have also found that in the Arequipa-Tacna area, the depth of the earthquakes in relation to the time of arrival, also fits an ARIMA model (1,1,0). We have used data from the Geophysical Institute of Peru, in particular, time, latitude, altitude, magnitude, depth, among others, the same that can be found on its website of the institution.El objetivo del presente trabajo es caracterizar y buscar patrones de comportamiento, en zonas con agrupamiento de sismos, mediante el uso de series de tiempo y los datos de los sismos ocurridos en el Perú en los años 2017 y 2018. En este trabajo exploratorio, primero hemos usado Cluster Analysis para formar grupos o áreas geográficas con cercanía de ocurrencia de sismos. Luego hemos encontrado que la magnitud de los sismos en el tiempo, evaluadas por zonas de cercanía geográficas, estaría correlacionada con la magnitud del sismo anterior, de ahí que haya resultado adecuado utilizar el modelo ARIMA (1,1,0), en el cual se considera un rezago y una diferencia para eliminar la presencia de alguna tendencia, sin la presencia de media móvil. Hemos identificado ocho zonas geográficas, en las cuales se agrupan los sismos. Entre otros resultados hemos hallado que en las zonas Arequipa-Tacna y Lima-Ica, las magnitudes de los sismos en relación con el tiempo de llegada, se ajustan a un modelo ARIMA(1,1,0). Por otro lado, también hemos hallado que en la zona de Arequipa-Tacna, la Pro-fundidad de los sismos en relación con el tiempo de llegada, se ajusta también a un modelo ARIMA(1,1,0). Hemos usado datos del Instituto Geofísico del Perú, en particular, el tiempo, latitud, altitud, magnitud, profundidad, entre otros, los mismos que se pueden encontrar en su página web de la institución.Universidad Nacional de Ingeniería2018-11-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionPeer ReviewedEvaluado por paresapplication/pdfaudio/mpegaudio/mpeghttps://revistas.uni.edu.pe/index.php/iecos/article/view/117310.21754/iecos.v19i0.1173revista IECOS; Vol. 19 (2018); 121-134Revista IECOS; Vol. 19 (2018); 121-1342788-74802961-284510.21754/iecos.v19i0reponame:Revistas - Universidad Nacional de Ingenieríainstname:Universidad Nacional de Ingenieríainstacron:UNIspaenghttps://revistas.uni.edu.pe/index.php/iecos/article/view/1173/3179https://revistas.uni.edu.pe/index.php/iecos/article/view/1173/3180https://revistas.uni.edu.pe/index.php/iecos/article/view/1173/3181Derechos de autor 2018 Carlos Risco Francohttps://creativecommons.org/licenses/by/4.0info:eu-repo/semantics/openAccessoai:oai:revistas.uni.edu.pe:article/11732025-01-20T08:36:45Z |
dc.title.none.fl_str_mv |
Time series analysis of earthquake data in Peru 2017-2018 Análisis de series de tiempo de datos de sismos en el Perú 2017-2018 |
title |
Time series analysis of earthquake data in Peru 2017-2018 |
spellingShingle |
Time series analysis of earthquake data in Peru 2017-2018 Risco Franco, Carlos sismos análisis de series de tiempo cluster analysis earthquakes time series analysis cluster analysis |
title_short |
Time series analysis of earthquake data in Peru 2017-2018 |
title_full |
Time series analysis of earthquake data in Peru 2017-2018 |
title_fullStr |
Time series analysis of earthquake data in Peru 2017-2018 |
title_full_unstemmed |
Time series analysis of earthquake data in Peru 2017-2018 |
title_sort |
Time series analysis of earthquake data in Peru 2017-2018 |
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 análisis de series de tiempo cluster analysis earthquakes time series analysis cluster analysis |
topic |
sismos análisis de series de tiempo cluster analysis earthquakes time series analysis cluster analysis |
description |
The objective of this work is to characterize and look for behavior patterns, in areas with earthquake clusters, through the use of time series and the data of the earthquakes that occurred in Peru in 2017 and 2018.In this exploratory work, we have first used Cluster Analysis to form groups or geographic areas with near earthquake occurrence. Then we have found that the magnitude of the earthquakes in time, evaluated by geographical proximity zones, would be correlated with the magnitude of the previous earthquake, hence it was appropriate to use the ARIMA model (1,1,0), in which It is considered a lag and a difference to eliminate the presence of some trend, without the presence of moving average. We have identified eight geographical areas, in which the earthquakes are grouped. Among other results we have found that in the Arequipa-Tacna and Lima-Ica areas, the magnitudes of the earthquakes in relation to the arrival time, conform to an ARIMA model (1,1,0). On the other hand, we have also found that in the Arequipa-Tacna area, the depth of the earthquakes in relation to the time of arrival, also fits an ARIMA model (1,1,0). We have used data from the Geophysical Institute of Peru, in particular, time, latitude, altitude, magnitude, depth, among others, the same that can be found on its website of the institution. |
publishDate |
2018 |
dc.date.none.fl_str_mv |
2018-11-01 |
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/1173 10.21754/iecos.v19i0.1173 |
url |
https://revistas.uni.edu.pe/index.php/iecos/article/view/1173 |
identifier_str_mv |
10.21754/iecos.v19i0.1173 |
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/1173/3179 https://revistas.uni.edu.pe/index.php/iecos/article/view/1173/3180 https://revistas.uni.edu.pe/index.php/iecos/article/view/1173/3181 |
dc.rights.none.fl_str_mv |
Derechos de autor 2018 Carlos Risco Franco https://creativecommons.org/licenses/by/4.0 info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
Derechos de autor 2018 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. 19 (2018); 121-134 Revista IECOS; Vol. 19 (2018); 121-134 2788-7480 2961-2845 10.21754/iecos.v19i0 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 |
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13.871978 |
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).