Finding possible precursors for the 2015 Cotopaxi Volcano eruption using unsupervised machine learning techniques
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Date
2019
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Abstract
Cotopaxi Volcano showed an increased activity since April 2015 and evolved into its eventual mild eruption in August 2015. In this work we use records from a broadband seismic station located at less than 4 km from the vent that encompass data from April to December of 2015, to detect and study low-frequency seismic events. We applied unsupervised learning schemes to group and identify possible premonitory low-frequency seismic families. To find these families we applied a two-stage process in which the events were first separated by their frequency content by applying the k-means algorithm to the spectral density vector of the signals and then were further separated by their waveform by applying Correntropy and Dynamic Time Warping. As a result, we found a particular family related to the volcano’s state of activity by exploring its time distribution and estimating its events’ locations.
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Keywords
Erupciones volcánicas, Geodinámica