Please use this identifier to cite or link to this item:
http://hdl.handle.net/2122/5083
DC Field | Value | Language |
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dc.contributor.authorall | Langer, H.; Istituto Nazionale di Geofisica e Vulcanologia, Sezione Catania, Catania, Italia | en |
dc.contributor.authorall | Falsaperla, S.; Istituto Nazionale di Geofisica e Vulcanologia, Sezione Catania, Catania, Italia | en |
dc.contributor.authorall | Masotti, M.; Medical Imaging Group, Department of Physics, University of Bologna | en |
dc.contributor.authorall | Campanini, R.; Medical Imaging Group, Department of Physics, University of Bologna | en |
dc.contributor.authorall | Spampinato, S.; Istituto Nazionale di Geofisica e Vulcanologia, Sezione Catania, Catania, Italia | en |
dc.contributor.authorall | Messina, A.; Istituto Nazionale di Geofisica e Vulcanologia, Sezione Roma2, Roma, Italia | en |
dc.date.accessioned | 2009-06-23T10:49:01Z | en |
dc.date.available | 2009-06-23T10:49:01Z | en |
dc.date.issued | 2009-03-10 | en |
dc.identifier.uri | http://hdl.handle.net/2122/5083 | en |
dc.description.abstract | States of volcanic activity at Mt Etna develop in well-defined regimes with variable duration from a few hours to several months. Changes in the regimes are usually concurrent with variations of the characteristics of volcanic tremor, which is continuously recorded as background seismic radiation. This strict relationship is useful for monitoring volcanic activity in any moment and in whatever condition.We investigated the development of tremor features and its relation to regimes of volcanic activity applying pattern classification techniques. We present results from supervised and unsupervised classification methods applied to 425 patterns of volcanic tremor recorded between 2001 July and August, when a volcano unrest occurred. Support Vector Machine (SVM) and multilayer perceptron (MLP) were used as pattern classifiers with supervised learning. For the SVM and MLP training, we considered four target classes, that is, pre-eruptive, lava fountains, eruptive and post-eruptive. Using a leave one out testing scheme, SVM reached a score of 94.8 per cent of patterns matching the actual class membership, whereas MLP achieved 81.9 per cent of matching patterns. The excellent results, in particular those obtained with SVM, confirmed the reproducibility of the a priori classification. Unsupervised classification was carried out using cluster analysis (CA) and self-organizing maps (SOM). The clusters identified in unsupervised classification formed well-defined regimes, which can be easily related to the four a priori classes aforementioned. Besides, CA found a further cluster concurrent with the climax of eruptive activity. Applying a proper colour-coding to the microclusters (the so-called best matching units) identified by SOM, it was visually possible to follow the development of the characteristics of the tremor data with time, highlighting transitional stages from a regime of volcanic activity to another one. We conclude that supervised and unsupervised classification methods can be conveniently implemented as complementary tools for an in-depth understanding of the relationships between tremor data and volcanic phenomena. | en |
dc.language.iso | English | en |
dc.relation.ispartof | Geophys. J. Int. | en |
dc.relation.ispartofseries | 2/178 (2009) | en |
dc.subject | neural networks | en |
dc.subject | fuzzy logic | en |
dc.subject | persistance | en |
dc.subject | memory | en |
dc.subject | correlations | en |
dc.subject | clustering | en |
dc.subject | Volcano seismology | en |
dc.subject | Statistical seismology | en |
dc.subject | Volcano monitoring | en |
dc.title | Synopsis of supervised and unsupervised pattern classification techniques applied to volcanic tremor data atMt Etna, Italy | en |
dc.type | article | en |
dc.description.status | Published | en |
dc.type.QualityControl | Peer-reviewed | en |
dc.description.pagenumber | 1132 - 1144 | en |
dc.subject.INGV | 04. Solid Earth::04.06. Seismology::04.06.08. Volcano seismology | en |
dc.subject.INGV | 04. Solid Earth::04.06. Seismology::04.06.09. Waves and wave analysis | en |
dc.subject.INGV | 04. Solid Earth::04.06. Seismology::04.06.10. Instruments and techniques | en |
dc.subject.INGV | 04. Solid Earth::04.08. Volcanology::04.08.06. Volcano monitoring | en |
dc.subject.INGV | 05. General::05.01. Computational geophysics::05.01.01. Data processing | en |
dc.subject.INGV | 05. General::05.01. Computational geophysics::05.01.02. Cellular automata, fuzzy logic, genetic alghoritms, neural networks | en |
dc.subject.INGV | 05. General::05.01. Computational geophysics::05.01.04. Statistical analysis | en |
dc.subject.INGV | 05. General::05.01. Computational geophysics::05.01.05. Algorithms and implementation | en |
dc.identifier.doi | 10.1111/j.1365-246X.2009.04179.x | en |
dc.relation.references | Alparone, S., Andronico, D., Lodato, L. & Sgroi, T., 2003. Relationship between tremor and volcanic activity during the Southeast Crater eruption on Mount Etna in early 2000, J. geophys. Res., 108(B5), 2241, doi:10.1029/2002JB001866. Anderberg, M.R., 1973. Cluster Analysis for Applications, Academic Press, New York, 359 pp. Barron, A., 1993. Universal approximation bounds for superposition of a sigmoidal function, IEEE Trans. Information Theory, 39, 930–945. Behncke, B. & Neri, M., 2003a. Cycles and trends in the recent eruptive behavior of Mount Etna (Ital), Can. J. Earth Sci., 40, 1405–1411. Behncke, B. & Neri,M., 2003b. The July–August 2001 eruption ofMt. Etna (Sicily), Bull. Volcanol., 65, 461–476, doi:10.1007/s00445–003-0274–1. Bishop, C.M., 1995. Neural Networks for Pattern Recognition, Oxford University Press, Oxford, 482 pp. Bonaccorso, A., Calvari, S., Coltelli, M., Del Negro, C. & Falsaperla, S. (Eds), 2004. Mt. Etna: Volcano Laboratory, Geophys. Monogr. Ser, Vol. 143, pp. 384, AGU, Washington, DC. Cybenko, G., 1989. Approximation by super precisions of a sigmoidal function, Math. Control Signal, 2, 303–314, doi:10.1007/BF02551274. Duda, O.D., Hart, P.E. & Stork, D.G., 2001. Pattern Classification, John Wiley and Sons, New York, 654 pp. Efron,B.&Tibshirani, R.J., 1993. An introduction to the bootstrap, in Monographs on Statistics and Applied Probability, Vol. 57, 436 pp, Chapman & Hall, London. Falsaperla, S., Langer, H. & Spampinato, S., 1998. Statistical analyses and characteristics of volcanic tremor on Stromboli volcano. Bull. Volcanol., 60/2, 75–88. Falsaperla, S., Alparone, S., D’Amico, S., Di Grazia, G., Ferrari, F., Langer, H., Sgroi, T. & Spampinato, S., 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. Freeman, J.A. & Skapura, D.M., 1992. Neural Networks—Algorithms, Applications and Programming Techniques, Addison-Wesley Publishing Company, Inc., Reading, MA. Gillot, P.Y., Kieffer, G. & Romano, R., 1994. The evolution of Mount Etna in the light of potassium argon dating, Acta Vulcanol., 5, 81–87. Hastie, T., Tibshirani, R. & Friedman, J., 2002. The Elements of Statistical Learning, Springer-Verlag, Berlin, 533 pp. Holland, J.H., 1962. Outline for a logical theory of adaptive systems, J. Assoc. Comput.Mach., 3, 297–314. Kirkpatrick, S., Gelatt, C.D. Jr & Vecchi, M.P., 1983. Optimization by simulated annealing, Science, 220, 671–680. Kohonen, T., 1984. Self-organization and associative memory, Springer Series in Information Sciences, 1st edn, Vol. 8, Springer-Verlag, New York. Kohonen, T., 2001. Self Organizing Maps, 3rd edn, Springer, Berlin, 501 pp. Langer, H., Falsaperla, S., 2003. Seismic monitoring at Stromboli Volcano (Italy). A case study for data reduction and parameter extraction, J. Volcanol. Geoth. Res., 128, 233–245. Masotti, M., Falsaperla, S., Langer, H., Spampinato, S. & Campanini, R., 2006. Application of Support Vector Machine to the classification of volcanic tremor at Etna, Italy, Geophys. Res. Lett., 33, L20304, doi:10.1029/2006GL027441. Masotti, M., Campanini, R., Mazzacurati, L., Falsaperla, S., Langer, H. & Spampinato, S., 2008. TREMOrEC: a software utility for automatic classification of volcanic tremor, Geochem. Geophys. Geosyst., 9, Q04007, doi:10.1029/2007GC001860. Patan`e, D. et al., 2003. Seismological features and kinematic constraints for the July–August 2001 lateral eruption at Mt. Etna Volcano, Italy, Ann. Geophys., 46(4), 599–608. Patan`e, D., Cocina, O., Falsaperla, S., Privitera, E. & Spampinato, S., 2004. Mt. Etna volcano: a seismological framework, in Mt. Etna: Volcano Laboratory, Vol. 143, pp. 147–165, eds Bonacorso, A., Calvari, S., Coltelli, M.,Del Negro, C.&Falsaperla, S.,AGU, Geophys.Monogr. Ser., Washington, DC. Research staff of INGV, Sez. di Catania, 2001. Multidisciplinary approach yields insight into Mt. Etna eruption, EOS, Trans. AGU, 82(52), 653, 656. Rumelhart, D.E., Hinton, G.E. & Williams, R.J., 1986. Learning representations by back propagating errors, Nature, 323, 533–536. Sp¨ath, H., 1983. Cluster-Formation und Analyse, Theorie, FORTRANProgramme, Beispiele, Oldenbourg, M¨unchen. Vapnik, V., 1998. Statistical Learning Theory, Wiley and Sons, Inc., NewYork. Vesanto, J., Himberg, J., Alhoniemi, E. & Parhankangas, J., 2000. SOM Toolbox for Matalab 5, Report A57, http://www.cis.hut.fi/ projects/somtoolbox. Weston, J. & Watkins, C., 1999. Multi-class support vector machines, in Proceedings of ESANN99, ed. Verleysen, M., D. Facto Press, Brussels. | en |
dc.description.obiettivoSpecifico | 1.4. TTC - Sorveglianza sismologica delle aree vulcaniche attive | en |
dc.description.obiettivoSpecifico | 1.5. TTC - Sorveglianza dell'attività eruttiva dei vulcani | en |
dc.description.journalType | JCR Journal | en |
dc.description.fulltext | reserved | en |
dc.contributor.author | Langer, H. | en |
dc.contributor.author | Falsaperla, S. | en |
dc.contributor.author | Masotti, M. | en |
dc.contributor.author | Campanini, R. | en |
dc.contributor.author | Spampinato, S. | en |
dc.contributor.author | Messina, A. | 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 | Medical Imaging Group, Department of Physics, University of Bologna | en |
dc.contributor.department | Medical Imaging Group, Department of Physics, University of Bologna | 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, Sezione Roma2, Roma, Italia | 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 | 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.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.orcid | 0000-0002-2508-8067 | - |
crisitem.author.orcid | 0000-0002-1071-3958 | - |
crisitem.author.orcid | 0000-0002-1954-1080 | - |
crisitem.author.orcid | 0000-0002-3358-7210 | - |
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.author.parentorg | Istituto Nazionale di Geofisica e Vulcanologia | - |
crisitem.classification.parent | 04. Solid Earth | - |
crisitem.classification.parent | 04. Solid Earth | - |
crisitem.classification.parent | 04. Solid Earth | - |
crisitem.classification.parent | 04. Solid Earth | - |
crisitem.classification.parent | 05. General | - |
crisitem.classification.parent | 05. General | - |
crisitem.classification.parent | 05. General | - |
crisitem.classification.parent | 05. General | - |
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 | - |
crisitem.department.parentorg | Istituto Nazionale di Geofisica e Vulcanologia | - |
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