Fast Determination of Earthquake Depth Using Seismic Records of a Single Station, Implementing Machine Learning Techniques
The purpose of this research is to apply a new approach to make a fast determination of earthquake depth using seismic records of the “El Rosal” station, near to the city of Bogota – Colombia, by applying support vector machine regression (SVMR). The algorithm was trained with descriptors obtained f...
- Autores:
-
Ochoa Gutierrez, Luis Hernán
Niño Vasquez, Luis Fernando
Vargas Jimenez, Carlos Alberto
- Tipo de recurso:
- Article of journal
- Fecha de publicación:
- 2018
- Institución:
- Universidad Nacional de Colombia
- Repositorio:
- Universidad Nacional de Colombia
- Idioma:
- spa
- OAI Identifier:
- oai:repositorio.unal.edu.co:unal/67536
- Acceso en línea:
- https://repositorio.unal.edu.co/handle/unal/67536
http://bdigital.unal.edu.co/68565/
- Palabra clave:
- 62 Ingeniería y operaciones afines / Engineering
Earthquake Early Warning
Rapid Response
Earthquake Depth
Seismic Event
Bogota – Colombia
Support Vector Machine Regression (SVMR)
Seismology
Earthquakes.
Alerta Temprana de Terremoto
Respuesta Rápida
Profundidad de un Terremoto
Evento Sísmico
Bogotá - Colombia
Máquinas de Soporte Vectorial (MSV)
Sismología
Terremotos
- Rights
- openAccess
- License
- Atribución-NoComercial 4.0 Internacional
| id |
UNACIONAL2_93104d7e0d8a627784636b1eace16e5f |
|---|---|
| oai_identifier_str |
oai:repositorio.unal.edu.co:unal/67536 |
| network_acronym_str |
UNACIONAL2 |
| network_name_str |
Universidad Nacional de Colombia |
| repository_id_str |
|
| dc.title.spa.fl_str_mv |
Fast Determination of Earthquake Depth Using Seismic Records of a Single Station, Implementing Machine Learning Techniques |
| title |
Fast Determination of Earthquake Depth Using Seismic Records of a Single Station, Implementing Machine Learning Techniques |
| spellingShingle |
Fast Determination of Earthquake Depth Using Seismic Records of a Single Station, Implementing Machine Learning Techniques 62 Ingeniería y operaciones afines / Engineering Earthquake Early Warning Rapid Response Earthquake Depth Seismic Event Bogota – Colombia Support Vector Machine Regression (SVMR) Seismology Earthquakes. Alerta Temprana de Terremoto Respuesta Rápida Profundidad de un Terremoto Evento Sísmico Bogotá - Colombia Máquinas de Soporte Vectorial (MSV) Sismología Terremotos |
| title_short |
Fast Determination of Earthquake Depth Using Seismic Records of a Single Station, Implementing Machine Learning Techniques |
| title_full |
Fast Determination of Earthquake Depth Using Seismic Records of a Single Station, Implementing Machine Learning Techniques |
| title_fullStr |
Fast Determination of Earthquake Depth Using Seismic Records of a Single Station, Implementing Machine Learning Techniques |
| title_full_unstemmed |
Fast Determination of Earthquake Depth Using Seismic Records of a Single Station, Implementing Machine Learning Techniques |
| title_sort |
Fast Determination of Earthquake Depth Using Seismic Records of a Single Station, Implementing Machine Learning Techniques |
| dc.creator.fl_str_mv |
Ochoa Gutierrez, Luis Hernán Niño Vasquez, Luis Fernando Vargas Jimenez, Carlos Alberto |
| dc.contributor.author.spa.fl_str_mv |
Ochoa Gutierrez, Luis Hernán Niño Vasquez, Luis Fernando Vargas Jimenez, Carlos Alberto |
| dc.subject.ddc.spa.fl_str_mv |
62 Ingeniería y operaciones afines / Engineering |
| topic |
62 Ingeniería y operaciones afines / Engineering Earthquake Early Warning Rapid Response Earthquake Depth Seismic Event Bogota – Colombia Support Vector Machine Regression (SVMR) Seismology Earthquakes. Alerta Temprana de Terremoto Respuesta Rápida Profundidad de un Terremoto Evento Sísmico Bogotá - Colombia Máquinas de Soporte Vectorial (MSV) Sismología Terremotos |
| dc.subject.proposal.spa.fl_str_mv |
Earthquake Early Warning Rapid Response Earthquake Depth Seismic Event Bogota – Colombia Support Vector Machine Regression (SVMR) Seismology Earthquakes. Alerta Temprana de Terremoto Respuesta Rápida Profundidad de un Terremoto Evento Sísmico Bogotá - Colombia Máquinas de Soporte Vectorial (MSV) Sismología Terremotos |
| description |
The purpose of this research is to apply a new approach to make a fast determination of earthquake depth using seismic records of the “El Rosal” station, near to the city of Bogota – Colombia, by applying support vector machine regression (SVMR). The algorithm was trained with descriptors obtained from time signals of 863 seismic events acquired between January 1998 and October 2008; only earthquakes with magnitude ≥ 2 were contemplated, filtering its signals to remove diverse kind of noises not related to earth tremors. During training stages of SVMR several combinations of kernel function exponent and complexity factor were considered for time signals of 5, 10 and 15 seconds along with earthquake magnitudes of 2.0, 2.5, 3.0 and 3.5 (Ml). The best classification of SVMR was obtained using time signals of 15 seconds and earthquake magnitudes of 3.5 with kernel exponent of 10 and complexity factor of 2, showing accuracy of 0.6 ± 16.5 kilometers, which is good enough to be used in an early warning system for the city of Bogota. It is recommended to provide this model with a previous phase of deep-shallow classification. |
| publishDate |
2018 |
| dc.date.issued.spa.fl_str_mv |
2018-05-01 |
| dc.date.accessioned.spa.fl_str_mv |
2019-07-03T04:29:14Z |
| dc.date.available.spa.fl_str_mv |
2019-07-03T04:29:14Z |
| dc.type.spa.fl_str_mv |
Artículo de revista |
| dc.type.coar.fl_str_mv |
http://purl.org/coar/resource_type/c_2df8fbb1 |
| dc.type.driver.spa.fl_str_mv |
info:eu-repo/semantics/article |
| dc.type.version.spa.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
| dc.type.coar.spa.fl_str_mv |
http://purl.org/coar/resource_type/c_6501 |
| dc.type.coarversion.spa.fl_str_mv |
http://purl.org/coar/version/c_970fb48d4fbd8a85 |
| dc.type.content.spa.fl_str_mv |
Text |
| dc.type.redcol.spa.fl_str_mv |
http://purl.org/redcol/resource_type/ART |
| format |
http://purl.org/coar/resource_type/c_6501 |
| status_str |
publishedVersion |
| dc.identifier.issn.spa.fl_str_mv |
ISSN: 2248-8723 |
| dc.identifier.uri.none.fl_str_mv |
https://repositorio.unal.edu.co/handle/unal/67536 |
| dc.identifier.eprints.spa.fl_str_mv |
http://bdigital.unal.edu.co/68565/ |
| identifier_str_mv |
ISSN: 2248-8723 |
| url |
https://repositorio.unal.edu.co/handle/unal/67536 http://bdigital.unal.edu.co/68565/ |
| dc.language.iso.spa.fl_str_mv |
spa |
| language |
spa |
| dc.relation.spa.fl_str_mv |
https://revistas.unal.edu.co/index.php/ingeinv/article/view/68407 |
| dc.relation.ispartof.spa.fl_str_mv |
Universidad Nacional de Colombia Revistas electrónicas UN Ingeniería e Investigación Ingeniería e Investigación |
| dc.relation.references.spa.fl_str_mv |
Ochoa Gutierrez, Luis Hernán and Niño Vasquez, Luis Fernando and Vargas Jimenez, Carlos Alberto (2018) Fast Determination of Earthquake Depth Using Seismic Records of a Single Station, Implementing Machine Learning Techniques. Ingeniería e Investigación, 38 (2). pp. 91-103. ISSN 2248-8723 |
| dc.rights.spa.fl_str_mv |
Derechos reservados - Universidad Nacional de Colombia |
| dc.rights.coar.fl_str_mv |
http://purl.org/coar/access_right/c_abf2 |
| dc.rights.license.spa.fl_str_mv |
Atribución-NoComercial 4.0 Internacional |
| dc.rights.uri.spa.fl_str_mv |
http://creativecommons.org/licenses/by-nc/4.0/ |
| dc.rights.accessrights.spa.fl_str_mv |
info:eu-repo/semantics/openAccess |
| rights_invalid_str_mv |
Atribución-NoComercial 4.0 Internacional Derechos reservados - Universidad Nacional de Colombia http://creativecommons.org/licenses/by-nc/4.0/ http://purl.org/coar/access_right/c_abf2 |
| eu_rights_str_mv |
openAccess |
| dc.format.mimetype.spa.fl_str_mv |
application/pdf |
| dc.publisher.spa.fl_str_mv |
Universidad Nacional de Colombia - Sede Bogotá - Facultad de Ingeniería |
| institution |
Universidad Nacional de Colombia |
| bitstream.url.fl_str_mv |
https://repositorio.unal.edu.co/bitstream/unal/67536/1/68407-393153-1-PB.pdf https://repositorio.unal.edu.co/bitstream/unal/67536/2/68407-393153-1-PB.pdf.jpg |
| bitstream.checksum.fl_str_mv |
44ad89c71a4e18f252c1e6024bf1d4e6 71b97f0363696975db2aa2cbae1a8827 |
| bitstream.checksumAlgorithm.fl_str_mv |
MD5 MD5 |
| repository.name.fl_str_mv |
Repositorio Institucional Universidad Nacional de Colombia |
| repository.mail.fl_str_mv |
repositorio_nal@unal.edu.co |
| _version_ |
1814089724764094464 |
| spelling |
Atribución-NoComercial 4.0 InternacionalDerechos reservados - Universidad Nacional de Colombiahttp://creativecommons.org/licenses/by-nc/4.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Ochoa Gutierrez, Luis Hernán294c1675-bfc7-4900-9f22-e05288f15bcd300Niño Vasquez, Luis Fernando6335a811-aa46-47b5-9e67-5f63e6e25b14300Vargas Jimenez, Carlos Albertoc5cb462f-7dab-464b-9234-270906198d9e3002019-07-03T04:29:14Z2019-07-03T04:29:14Z2018-05-01ISSN: 2248-8723https://repositorio.unal.edu.co/handle/unal/67536http://bdigital.unal.edu.co/68565/The purpose of this research is to apply a new approach to make a fast determination of earthquake depth using seismic records of the “El Rosal” station, near to the city of Bogota – Colombia, by applying support vector machine regression (SVMR). The algorithm was trained with descriptors obtained from time signals of 863 seismic events acquired between January 1998 and October 2008; only earthquakes with magnitude ≥ 2 were contemplated, filtering its signals to remove diverse kind of noises not related to earth tremors. During training stages of SVMR several combinations of kernel function exponent and complexity factor were considered for time signals of 5, 10 and 15 seconds along with earthquake magnitudes of 2.0, 2.5, 3.0 and 3.5 (Ml). The best classification of SVMR was obtained using time signals of 15 seconds and earthquake magnitudes of 3.5 with kernel exponent of 10 and complexity factor of 2, showing accuracy of 0.6 ± 16.5 kilometers, which is good enough to be used in an early warning system for the city of Bogota. It is recommended to provide this model with a previous phase of deep-shallow classification.El propósito de esta investigación es aplicar métodos de máquinas de vector de soporte (MVS) para determinar rápidamente las profundidades de terremotos utilizando registros sísmicos de la estación El Rosal, cerca de la ciudad de Bogotá – Colombia. El algoritmo fue entrenado con descriptores de señales de tiempo de 863 eventos sísmicos adquiridos entre enero de 1998 y octubre de 2008; solo se contemplaron terremotos de magnitudes ≥ 2 M_L, filtrando sus señales para remover diversos tipos de ruidos no relacionados con temblores terrestres. Durante las etapas de entrenamiento de la MVS varias combinaciones del exponente de la función kernel y factor de complejidad fueron considerados para señales de tiempo de 5, 10 y 15 segundos junto con terremotos de magnitudes 2.0, 2.5, 3.0 y 3.5 M_L. La mejor clasificación de la MVS fue obtenida utilizando señales de tiempo de 15 segundos y terremotos de magnitudes 3.5 M_L con exponente kernel de 10 y factor de complejidad de 2, mostrando precisión de 0,6 ± 16,5 kilómetros, lo cual es suficientemente bueno para ser utilizado en un sistema de alerta temprana para la ciudad de Bogotá. Se recomienda proveer este modelo con eventos sísmicos recientes, con la finalidad de mejorar su precisión.application/pdfspaUniversidad Nacional de Colombia - Sede Bogotá - Facultad de Ingenieríahttps://revistas.unal.edu.co/index.php/ingeinv/article/view/68407Universidad Nacional de Colombia Revistas electrónicas UN Ingeniería e InvestigaciónIngeniería e InvestigaciónOchoa Gutierrez, Luis Hernán and Niño Vasquez, Luis Fernando and Vargas Jimenez, Carlos Alberto (2018) Fast Determination of Earthquake Depth Using Seismic Records of a Single Station, Implementing Machine Learning Techniques. Ingeniería e Investigación, 38 (2). pp. 91-103. ISSN 2248-872362 Ingeniería y operaciones afines / EngineeringEarthquake Early WarningRapid ResponseEarthquake DepthSeismic EventBogota – ColombiaSupport Vector Machine Regression (SVMR)SeismologyEarthquakes.Alerta Temprana de TerremotoRespuesta RápidaProfundidad de un TerremotoEvento SísmicoBogotá - ColombiaMáquinas de Soporte Vectorial (MSV)SismologíaTerremotosFast Determination of Earthquake Depth Using Seismic Records of a Single Station, Implementing Machine Learning TechniquesArtículo de revistainfo:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501http://purl.org/coar/resource_type/c_2df8fbb1http://purl.org/coar/version/c_970fb48d4fbd8a85Texthttp://purl.org/redcol/resource_type/ARTORIGINAL68407-393153-1-PB.pdfapplication/pdf705769https://repositorio.unal.edu.co/bitstream/unal/67536/1/68407-393153-1-PB.pdf44ad89c71a4e18f252c1e6024bf1d4e6MD51THUMBNAIL68407-393153-1-PB.pdf.jpg68407-393153-1-PB.pdf.jpgGenerated Thumbnailimage/jpeg8335https://repositorio.unal.edu.co/bitstream/unal/67536/2/68407-393153-1-PB.pdf.jpg71b97f0363696975db2aa2cbae1a8827MD52unal/67536oai:repositorio.unal.edu.co:unal/675362023-05-30 23:03:02.535Repositorio Institucional Universidad Nacional de Colombiarepositorio_nal@unal.edu.co |