Pattern recognition applied to seismic signals of the Llaima volcano (Chile): An analysis of the events’ features

C. San Martin, Millaray Curilem, Jorge Vergara, Gustavo Fuentealba, Carlos Cardona, Fernando Huenupan, Max Chacón, M Salman Khan, Walid Hussein and Nestor Becerra Yoma


This paper proposes a computer-based classifier to automatically identify four seismic event classes of the Llaima volcano, one of the most active volcanoes in the Southern Andes, situated in the Araucanía Region of Chile. A combination of features that provided good recognition performance in our previous papers concerning the Llaima and Villarica (located 100 km south of Llaima) volcanoes is utilized in order to train the classifiers. These features are extracted from the amplitude, frequency and phase of the seismic signals. Unlike the previous works where fixed length windows were used to obtain the seismic signals, this paper employs signals of variable lengths that span the entire seismic event. The classifiers are implemented using support vector machines. A confidence analysis is also included to improve reliability of the classification. Results indicate that the features used for recognition of the events of Villarica volcano also provide good recognition results for the Llaima volcano, yielding classification exactitude of over 80%.


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