Publication Date:
2017-04-04
Description:
We describe a stand-alone software utility named TREMOrEC, which carries out training and test of a Support Vector Machine (SVM) classifier. TREMOrEC is developed in Visual C++ and runs under Microsoft Windows operating systems. Ease of use and short time processing, along with the excellent performance of the SVM classifier, make this tool ideal for volcano monitoring. The development of TREMOrEC is motivated by the successful application of the SVM classifier to volcanic tremor data recorded at Mount Etna in 2001 [Masotti et al,. 2006]. In that application, spectrograms of volcanic tremor were divided according to their recording date into four classes associated with different states of activity, i.e., pre-eruptive, lava fountain, eruptive, or post-eruptive. During the training, SVM learned the a-priori classification. The classifier’s performance was then evaluated on test sets not considered for training. The classification results matched the actual class membership with less than 6% of error.
Description:
Istituto Nazionale di Geofisica e Vulcanologia and Dipartimento per la Protezione Civile (projects V4/02 and V4/03).
Description:
Published
Description:
Q04007
Description:
1.4. TTC - Sorveglianza sismologica delle aree vulcaniche attive
Description:
JCR Journal
Description:
reserved
Keywords:
Volcanic tremor
;
Etna
;
Support Vector Machine
;
classification
;
04. Solid Earth::04.06. Seismology::04.06.08. Volcano seismology
Repository Name:
Istituto Nazionale di Geofisica e Vulcanologia (INGV)
Type:
article
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