Time series analysis of earthquake data in Peru 2017-2018

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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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Detalles Bibliográficos
Autor: Risco Franco, Carlos
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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spelling 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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