Non-supervised classification of volcanic-seismic events for Tungurahua-Volcano Ecuador
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Abstract
In this paper we propose the use of self-organizing maps and archetypal analysis as an method of unsupervised classification of seismic signals. Using this method we analyzed the record of seismic events for Tungurahua-Volcano (Ecuador) for the year 2014, obtained by a permanent geophysical station from Instituto Geofísico EPN located at the volcano. In standard volcanic monitoring procedures there exists a classification for seismic events performed in a supervised manner (a human being assigns a class to each event based on perception and some fixed criteria). However, even if this classification yields some information on the possible ongoing volcanic processes inside a volcano, it is not determinant when used as a method to predict an actual volcanic eruption. The method proposed in this paper has several advantages over supervised classification by human or based on human classification of seismic signals, one is that it is fast and can be automatized without relying on human intervention, other is that correlates well with human classification for events that clearly mark a volcanic eruption, moreover it finds other cluster of events that could be examined further to established if they have a volcanic interpretation.