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dc.contributor.authorMus León, Sergi
dc.contributor.authorGutiérrez Escobar, Norma
dc.contributor.authorTous Liesa, Rubén
dc.contributor.authorOtero Calviño, Beatriz
dc.contributor.authorCruz de la Cruz, Stalin Leonel
dc.contributor.authorLlácer Giner, David
dc.contributor.authorAlvarado Bermúdez, Leonardo
dc.contributor.authorRojas, Otilio
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament d'Arquitectura de Computadors
dc.date.accessioned2020-03-31T13:25:29Z
dc.date.available2020-03-31T13:25:29Z
dc.date.issued2019
dc.identifier.citationMus, S. [et al.]. Long short-term memory networks for earthquake detection in Venezuelan regions. A: International Conference on Machine Learning, Optimization, and Data Science. "Machine Learning, Optimization, and Data Science, 5th International Conference, LOD 2019: Siena, Italy, September 10-13, 2019: proceedings". Berlín: Springer, 2019, p. 751-754.
dc.identifier.isbn978-3-030-37599-7
dc.identifier.urihttp://hdl.handle.net/2117/182520
dc.description.abstractReliable earthquake detection and location algorithms are necessary to properly catalog and analyze the continuously growing seismic records. This paper reports the results of applying Long Short-Term Memory (LSTM) networks to single-station three-channel waveforms for P-wave earthquake detection in western and north central regions of Venezuela. Precisely, we apply our technique to study the seismicity along the dextral strike-slip Boconó and La Victoria - San Sebastián faults, with complex tectonics driven by the interactions between the South American and Caribbean plates.
dc.format.extent4 p.
dc.language.isoeng
dc.publisherSpringer
dc.subjectÀrees temàtiques de la UPC::Informàtica::Intel·ligència artificial
dc.subjectÀrees temàtiques de la UPC::Enginyeria civil::Geotècnia::Sismologia
dc.subject.lcshEarthquake prediction
dc.subject.lcshNeural networks (Computer science)
dc.subject.otherEarthquake detection
dc.subject.otherDeep learning
dc.subject.otherLSTM
dc.titleLong short-term memory networks for earthquake detection in Venezuelan regions
dc.typeConference lecture
dc.subject.lemacTerratrèmols -- Predicció
dc.subject.lemacXarxes neuronals (Informàtica)
dc.contributor.groupUniversitat Politècnica de Catalunya. CAP - Grup de Computació d'Altes Prestacions
dc.contributor.groupUniversitat Politècnica de Catalunya. VIRTUOS - Virtualisation and Operating Systems
dc.identifier.doi10.1007/978-3-030-37599-7_62
dc.description.peerreviewedPeer Reviewed
dc.relation.publisherversionhttps://link.springer.com/chapter/10.1007/978-3-030-37599-7_62
dc.rights.accessOpen Access
local.identifier.drac25845270
dc.description.versionPostprint (author's final draft)
dc.relation.projectidinfo:eu-repo/grantAgreement/MINECO//TIN2015-65316-P/ES/COMPUTACION DE ALTAS PRESTACIONES VII/
dc.relation.projectidinfo:eu-repo/grantAgreement/AGAUR/V PRI/2014 SGR 1051
local.citation.authorMus, S.; Gutierrez, N.; Tous, R.; Otero, B.; Cruz, L.; Llácer, D.; Alvarado, L.; Rojas, O.
local.citation.contributorInternational Conference on Machine Learning, Optimization, and Data Science
local.citation.pubplaceBerlín
local.citation.publicationNameMachine Learning, Optimization, and Data Science, 5th International Conference, LOD 2019: Siena, Italy, September 10-13, 2019: proceedings
local.citation.startingPage751
local.citation.endingPage754


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