Multi-station automatic classification of seismic signatures from the Lascar volcano database
Abstract k -fold cross-validation procedure. Under this approach, the results reached high predictive performance, considering that only the percentage of recognition of the tectonic events (TC) class was partially affected. The results obtained showed the performance of the probabilistic model, reaching high scores over different test datasets. The most valuable benefit of using this technique was that the use of volcano seismic signals from multiple stations provided a more generalizable model which, in the near future, can be extended to multi-volcano database systems. The impact of this work is significant in the evaluation of hazard and risk by monitoring the dynamic evolution of volcanic centers, which is crucial for understanding the stages in a volcano’s eruptive cycle.
- Standort
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Deutsche Nationalbibliothek Frankfurt am Main
- Umfang
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Online-Ressource
- Sprache
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Englisch
- Erschienen in
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Multi-station automatic classification of seismic signatures from the Lascar volcano database ; volume:23 ; number:2 ; year:2023 ; pages:991-1006 ; extent:16
Natural hazards and earth system sciences ; 23, Heft 2 (2023), 991-1006 (gesamt 16)
- Urheber
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Salazar, Pablo
Yupanqui, Franz
Meneses, Claudio
Layana, Susana
Yáñez, Gonzalo
- DOI
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10.5194/nhess-23-991-2023
- URN
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urn:nbn:de:101:1-2023033006095617233755
- Rechteinformation
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Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
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14.08.2025, 11:02 MESZ
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Beteiligte
- Salazar, Pablo
- Yupanqui, Franz
- Meneses, Claudio
- Layana, Susana
- Yáñez, Gonzalo
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