Please use this identifier to cite or link to this item:
http://hdl.handle.net/2122/2679
DC Field | Value | Language |
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dc.contributor.authorall | Masotti, M.; Medical Imaging Group, Department of Physics, University of Bologna, Bologna, Italy. | en |
dc.contributor.authorall | Falsaperla, S.; Istituto Nazionale di Geofisica e Vulcanologia, Sezione Catania, Catania, Italia | en |
dc.contributor.authorall | Langer, H.; Istituto Nazionale di Geofisica e Vulcanologia, Sezione Catania, Catania, Italia | en |
dc.contributor.authorall | Spampinato, S.; Istituto Nazionale di Geofisica e Vulcanologia, Sezione Catania, Catania, Italia | en |
dc.contributor.authorall | Campanin, R.; partment of Physics, University of Bologna, Bologna, Italy. | en |
dc.date.accessioned | 2007-10-15T13:37:25Z | en |
dc.date.available | 2007-10-15T13:37:25Z | en |
dc.date.issued | 2006 | en |
dc.identifier.uri | http://hdl.handle.net/2122/2679 | en |
dc.description.abstract | We applied an automatic pattern recognition technique, known as Support Vector Machine (SVM), to classify volcanic tremor data recorded during different states of activity at Etna volcano, Italy. The seismic signal was recorded at a station deployed 6 km southeast of the summit craters from 1 July to 15 August, 2001, a time span encompassing episodes of lava fountains and a 23 day-long effusive activity. Trained by a supervised learning algorithm, the classifier learned to recognize patterns belonging to four classes, i.e., pre-eruptive, lava fountains, eruptive, and posteruptive. Training and test of the classifier were carried out using 425 spectrogram-based feature vectors. Following cross-validation with a random subsampling strategy, SVM correctly classified 94.7 ± 2.4% of the data. The performance was confirmed by a leave-one-out strategy, with 401 matches out of 425 patterns. Misclassifications highlighted intrinsic fuzziness of class memberships of the signals, particularly during transitional phases. Citation: Masotti, M., S. Falsaperla, H. Langer, S. Spampinato, and R. Campanini (2006), Application of Support Vector Machine to the classification of volcanic tremor at Etna, Italy, Geophys. Res. Lett., 33, L20304, doi:10.1029/2006GL027441. | en |
dc.language.iso | English | en |
dc.relation.ispartof | GEOPHYSICAL RESEARCH LETTERS, | en |
dc.subject | Etna, | en |
dc.subject | classification | en |
dc.title | Application of Support Vector Machine to the classification of volcanic tremor at Etna, Italy | en |
dc.type | article | en |
dc.description.status | Published | en |
dc.type.QualityControl | Peer-reviewed | en |
dc.description.pagenumber | (L20304,) | en |
dc.subject.INGV | 04. Solid Earth::04.06. Seismology::04.06.08. Volcano seismology | en |
dc.identifier.doi | doi:10.1029/2006GL027441 | en |
dc.relation.references | Angelini, E., et al. (2006), Testing the performances of different image representations for mass classification in digital mammograms, Int. J. Mod. Phys. C, 17(1), 113– 131, doi:10.1142/S0129183106009199. Bazzani, A., et al. (2001), An SVM classifier to separate false signals from microcalcifications in digital mammograms, Phys. Med. Biol., 46(6), 1651– 1663, doi:10.1088/0031-9155/46/6/305. Behncke, B., and M. Neri (2003), The July –August 2001 eruption of Mt. Etna (Sicily), Bull. Volcanol., 65, 461–476, doi:10.1007/s00445- 003-0274-1. Campanini, R., et al. (2004), A novel featureless approach to mass detection in digital mammograms based on support vector machines, Phys. Med. Biol., 49(6), 961– 976, doi:10.1088/0031-9155/49/6/007. Duda, R. O., P. E. Hart, and D. G. Stork (2000), Pattern Classification, 654 pp., John Wiley, Hoboken, N. J. Efron, B., and R. J. Tibshirani (1993), An Introduction to the Bootstrap, CRC Press, Boca Raton, Fla. Falsaperla, S., et al. (2005), Volcanic tremor at Mt. Etna, Italy, preceding and accompanying the eruption of July– August, 2001, Pure Appl. Geophys., 162, 2111–2132, doi:10.1007/s00024-005-2710-y. Hastie, T., R. Tibshirani, and J. Friedman (2002), The Elements of Statistical Learning, 533 pp., Springer, New York. Langer, H., S. Falsaperla, and G. Thompson (2003), Application of Artificial Neural Networks for the classification of the seismic transients at Soufrie`re Hills volcano, Montserrat, Geophys. Res. Lett., 30(21), 2090, doi:10.1029/2003GL018082. Scarpetta, S., et al. (2005), Automatic classification of seismic signals at Mt. Vesuvius volcano, Italy, using neural networks, Bull. Seismol. Soc. Am., 95(1), 185– 196, doi:10.1785/0120030075. Vapnik, V. (1998), Statistical Learning Theory, John Wiley, Hoboken, N. J. Weston, J., and C. Watkins (1999), Multi-class support vector machines, in Proceedings of ESANN99, edited by M. Verleysen. pp. 219– 224, D. Facto Press, Brussels. R. Campanini and M. Masotti, Medical Imaging Group, Department of Physics, University of Bologna, Viale Berti-Pichat 6/2, I-40127, Bologna, Italy. S. Falsaperla, H. Langer, and S. Spampinato, Istituto Nazionale di Geofisica e Vulcanologia, Sezione di Catania, P.zza Roma 2, I-95123 Catania, Italy. (falsaperla@ct.ingv.it) | en |
dc.description.fulltext | reserved | en |
dc.contributor.author | Masotti, M. | en |
dc.contributor.author | Falsaperla, S. | en |
dc.contributor.author | Langer, H. | en |
dc.contributor.author | Spampinato, S. | en |
dc.contributor.author | Campanin, R. | en |
dc.contributor.department | Medical Imaging Group, Department of Physics, University of Bologna, Bologna, Italy. | en |
dc.contributor.department | Istituto Nazionale di Geofisica e Vulcanologia (INGV), Sezione OE, Catania, Italia | en |
dc.contributor.department | Istituto Nazionale di Geofisica e Vulcanologia (INGV), Sezione OE, Catania, Italia | en |
dc.contributor.department | Istituto Nazionale di Geofisica e Vulcanologia (INGV), Sezione OE, Catania, Italia | en |
dc.contributor.department | partment of Physics, University of Bologna, Bologna, Italy. | en |
item.openairetype | article | - |
item.cerifentitytype | Publications | - |
item.languageiso639-1 | en | - |
item.grantfulltext | restricted | - |
item.openairecristype | http://purl.org/coar/resource_type/c_18cf | - |
item.fulltext | With Fulltext | - |
crisitem.author.dept | Medical Imaging Group, Department of Physics, University of Bologna | - |
crisitem.author.dept | Istituto Nazionale di Geofisica e Vulcanologia (INGV), Sezione OE, Catania, Italia | - |
crisitem.author.dept | Istituto Nazionale di Geofisica e Vulcanologia (INGV), Sezione OE, Catania, Italia | - |
crisitem.author.dept | Istituto Nazionale di Geofisica e Vulcanologia (INGV), Sezione OE, Catania, Italia | - |
crisitem.author.dept | Medical Imaging Group, Department of Physics, University of Bologna | - |
crisitem.author.orcid | 0000-0002-1071-3958 | - |
crisitem.author.orcid | 0000-0002-2508-8067 | - |
crisitem.author.orcid | 0000-0002-1954-1080 | - |
crisitem.author.parentorg | Istituto Nazionale di Geofisica e Vulcanologia | - |
crisitem.author.parentorg | Istituto Nazionale di Geofisica e Vulcanologia | - |
crisitem.author.parentorg | Istituto Nazionale di Geofisica e Vulcanologia | - |
crisitem.classification.parent | 04. Solid Earth | - |
crisitem.department.parentorg | Istituto Nazionale di Geofisica e Vulcanologia | - |
crisitem.department.parentorg | Istituto Nazionale di Geofisica e Vulcanologia | - |
crisitem.department.parentorg | Istituto Nazionale di Geofisica e Vulcanologia | - |
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