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Application of K-means and Gaussian Mixture Model for Classification of Seismic Activities in Istanbul : Volume 19, Issue 4 (03/08/2012)

By Kuyuk, H. S.

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Book Id: WPLBN0003973219
Format Type: PDF Article :
File Size: Pages 9
Reproduction Date: 2015

Title: Application of K-means and Gaussian Mixture Model for Classification of Seismic Activities in Istanbul : Volume 19, Issue 4 (03/08/2012)  
Author: Kuyuk, H. S.
Volume: Vol. 19, Issue 4
Language: English
Subject: Science, Nonlinear, Processes
Collections: Periodicals: Journal and Magazine Collection (Contemporary), Copernicus GmbH
Historic
Publication Date:
2012
Publisher: Copernicus Gmbh, Göttingen, Germany
Member Page: Copernicus Publications

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Horasan, G., Dogan, E., Yildirim, E., & Kuyuk, H. S. (2012). Application of K-means and Gaussian Mixture Model for Classification of Seismic Activities in Istanbul : Volume 19, Issue 4 (03/08/2012). Retrieved from http://www.ebooklibrary.org/


Description
Description: Department of Civil Engineering, Sakarya University, Turkey. Two unsupervised pattern recognition algorithms, k-means, and Gaussian mixture model (GMM) analyses have been applied to classify seismic events in the vicinity of Istanbul. Earthquakes, which are occurring at different seismicity rates and extensions of the Thrace-Eskisehir Fault Zone and the North Anatolian Fault (NAF), Turkey, are being contaminated by quarries operated around Istanbul. We have used two time variant parameters, complexity, the ratio of integrated powers of the velocity seismogram, and S/P amplitude ratio as classifiers by using waveforms of 179 events (1.8 < M < 3.0). We have compared two algorithms with classical multivariate linear/quadratic discriminant analyses. The total accuracies of the models for GMM, k-means, linear discriminant function (LDF), and quadratic discriminant function (QDF) are 96.1%, 95.0%, 96.1%, 96.6%, respectively. The performances of models are discussed for earthquakes and quarry blasts separately. All methods clustered the seismic events acceptably where QDF slightly gave better improvements compared to others. We have found that unsupervised clustering algorithms, for which no a-prior target information is available, display a similar discriminatory power as supervised methods of discriminant analysis.

Summary
Application of k-means and Gaussian mixture model for classification of seismic activities in Istanbul

Excerpt
Baumgardt, D. R. and Young, G. B.: Regional seismic waveform discriminates and case-based event identification using regional arrays, B. Seismol. Soc. Am., 80, 1874–1892, 1990.; Bennett, T. J. and Murphy, J. R.: Analysis of seismic discrimination capabilities using regional data from western United States events, B. Seismol. Soc. Am., 76, 1069–1086, 1986.; Bennett, T. J., Barker, B. W., McLaughlin, K. L., and Murphy, J. R.: Regional discrimination of qarry blasts, earthquakes and underground nuclear explosions, Final Report, GL-TR-89-0114, S-Cubed, La Jolla, California, 1989.; Campus, P. and Fah, D..: Seismic monitoring of explosions: a method to extract information on the isotropic component of the seismic source, J. Seismol., 1, 205–218, doi:10.1023/A:1009781722363, 1997.; Del Pezzo, E., Esposito, A., Giudicepietro, F., Marinaro, M., Martini, M., and Scarpetta, S.: Discrimination of earthquakes and underwater explosions using neural Networks, B. Seismol. Soc. Am., 93, 215–223, 2003.; Dowla, F. U., Taylor, S. R., and Anderson, R. W.: Seismic discrimination with artificial neural networks: preliminary results with regional spectral data, B. Seismol. Soc. Am., 80, 1346–1373, 1990.; Duda, R. O., Hart, P. E., and Stork, D. G.: Pattern classification, ISBN SSN:0-471-05669-3, 2nd Edn., Wiley, New York, 2001.; Falsaperla, S., Graziani, S., Nunnari, G., and Spampinato, S.: Automatic classification of volcanic earthquakes by using multi-layered neural Networks, Nat. Hazards, 13, 205–228, 1996.; Gitterman, Y., Pinky, V., and Shapira, A.: Spectral classification methods in monitoring small local events by the Israel seismic network, J. Seismol., 2, 237–256, 1998.; Han, M., Zhao, Y., Li, G., and Reynolds, A. C.: Application of EM algorithms for seismic facices classification, Comput. Geosci., 15, 421–429, doi:10.1007/s10596-010-9212-4, 2011.; Hasselblad, V.: Estimation of Parameters for a Mixture of Normal Distributions, Technometrics, 8, 431–444, 1966.; Hasselblad, V.: Estimation of Finite Mixtures of Distributions from the Exponential Family, J. Am. Stat. Assoc., 64, 1459–1471, 1969.; Horasan, G., Bozepe-Güney, A., Küsmezer, A., Bekler, F., and Öǧütçü, Z.: \.{I}stanbul ve civarındaki deprem ve patlatma verilerinin birbirinden ayırt edilmesi ve kataoglanması (Discrimination and cataloging of quarry blasts and earthquakes in the vicinity of Istanbul), Report 05T202, Boǧaziçi University Research Foundation Bebek-\.{I}stanbul, 76 pp., 2006.; Horasan, G., Boztepe-Güney, A., Küsmezer, A., Bekler, F., Ögütçü, Z., and Musaoglu, N.: Contamination of seismicity catalogs by quarry blasts: an example from Istanbul and its vicinity, northwestern Turkey, J. Asian Earth Sci., 34, 90–99, doi:1016/j.jseaes.2008.0.012, 2009.; Jenkins, R. D. and Sereno, T. S.: Calibration of regional $\text{S}/\text{P}$ amplitude-ratio discriminants, Pure Appl. Geophys., 158, 1279–1300, doi:10.1007/PL00001223, 2001.; Koch, K. and Fah, D.: Identification of earthquakes and explosions using amplitude ratios: the Vogtland area revisited, Pure Appl. Geophys., 159, 735–757, 2002.; Kuyuk, H. S., Yıldırım, E., Dogan, E., and Horasan, G.: Self Organizing Map Approach for Discrimination of Seismic Event and Quarry Blasts in The Vicinity Of Istanbul, 14th European Conference on Earthquake Engineering, Ohrid, Republic of Macedonia, 30 August–3rd September, 2010.; Kuyuk, H. S., Yildirim, E., Dogan, E., and Horasan, G.: An unsupervised learning algorithm: application to the discrimination of seismic events and quarry blasts in the vicinity of Istanbul, Nat. Hazards Earth Syst. Sci., 11, 93–100, doi:10.5194/nhess-11-93-2011, 2011.; MacKay, D. J. C.: Information Theory, Inference, and Learning Algorithms, Ca

 

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