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Clustering Seismic Activities Using Linear and Nonlinear Discriminant Analysis

H Serdar Kuyuk Eray Yildirim Emrah Dogan Gunduz Horasan

H Serdar Kuyuk, Eray Yildirim, Emrah Dogan, Gunduz Horasan. Clustering Seismic Activities Using Linear and Nonlinear Discriminant Analysis[J]. Journal of Earth Science, 2014, 16(1): 140-145. doi: 10.1007/s12583-014-0406-x
引用本文: H Serdar Kuyuk, Eray Yildirim, Emrah Dogan, Gunduz Horasan. Clustering Seismic Activities Using Linear and Nonlinear Discriminant Analysis[J]. Journal of Earth Science, 2014, 16(1): 140-145. doi: 10.1007/s12583-014-0406-x
H Serdar Kuyuk, Eray Yildirim, Emrah Dogan, Gunduz Horasan. Clustering Seismic Activities Using Linear and Nonlinear Discriminant Analysis. Journal of Earth Science, 2014, 16(1): 140-145. doi: 10.1007/s12583-014-0406-x
Citation: H Serdar Kuyuk, Eray Yildirim, Emrah Dogan, Gunduz Horasan. Clustering Seismic Activities Using Linear and Nonlinear Discriminant Analysis. Journal of Earth Science, 2014, 16(1): 140-145. doi: 10.1007/s12583-014-0406-x

Clustering Seismic Activities Using Linear and Nonlinear Discriminant Analysis

doi: 10.1007/s12583-014-0406-x

Clustering Seismic Activities Using Linear and Nonlinear Discriminant Analysis

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出版历程
  • 收稿日期:  2014-01-16
  • 修回日期:  2014-01-16
  • 刊出日期:  2014-01-16

Clustering Seismic Activities Using Linear and Nonlinear Discriminant Analysis

doi: 10.1007/s12583-014-0406-x

摘要: Identification and classification of different seismo-tectonic events with similar characteristics in a region of interest is one of the most important subjects in seismic hazard studies. In this study, linear and nonlinear discriminant analyses have been applied to classify seismic events in the vicinity of Istanbul. The vertical components of the digital velocity seismograms are used for seismic events with magnitude (Md) between 1.8 and 3.0 that occurred between 2001 and 2004. Two, time dependent parameters, complexity and S/P peak amplitude ratio are selected as predictands. Linear, quadratic, diaglinear and diagquadratic discriminant functions are investigated. Accuracy of methods with an additional adjusted quadratic models are 96.6%, 96.6%, 95.5%, 96.6%, and 97.6%, respectively with a various misclassified rate for each class. The performances of models are justified with cross validation and resubstitution error. Although all models remarkably well performed, adjusted quadratic function achieved the best success rate with just 4 misclassified events out of 179, even better compared to complex methods such as, self organizing method, k-means, Gaussion mixture models that applied to same dataset in literature.

English Abstract

H Serdar Kuyuk, Eray Yildirim, Emrah Dogan, Gunduz Horasan. Clustering Seismic Activities Using Linear and Nonlinear Discriminant Analysis[J]. Journal of Earth Science, 2014, 16(1): 140-145. doi: 10.1007/s12583-014-0406-x
引用本文: H Serdar Kuyuk, Eray Yildirim, Emrah Dogan, Gunduz Horasan. Clustering Seismic Activities Using Linear and Nonlinear Discriminant Analysis[J]. Journal of Earth Science, 2014, 16(1): 140-145. doi: 10.1007/s12583-014-0406-x
H Serdar Kuyuk, Eray Yildirim, Emrah Dogan, Gunduz Horasan. Clustering Seismic Activities Using Linear and Nonlinear Discriminant Analysis. Journal of Earth Science, 2014, 16(1): 140-145. doi: 10.1007/s12583-014-0406-x
Citation: H Serdar Kuyuk, Eray Yildirim, Emrah Dogan, Gunduz Horasan. Clustering Seismic Activities Using Linear and Nonlinear Discriminant Analysis. Journal of Earth Science, 2014, 16(1): 140-145. doi: 10.1007/s12583-014-0406-x

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