NDLI: Clustering seismic activities using linear and nonlinear discriminant analysis

Content Provider	Springer Nature Link
Author	Kuyuk, H. Serdar Yildirim, Eray Dogan, Emrah Horasan, Gunduz
Copyright Year	2014
Abstract	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 (M $_{d}$) 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.
Starting Page	140
Ending Page	145
Page Count	6
File Format	PDF
ISSN	1674487X
Journal	Journal of Earth Science
Volume Number	25
Issue Number	1
e-ISSN	1867111X
Language	English
Publisher	Springer Berlin Heidelberg
Publisher Date	2014-01-24
Publisher Place	Berlin, Heidelberg
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	discriminant analysis clustering analysis self organizing map k-means Gaussion mixture models Earth Sciences Geotechnical Engineering & Applied Earth Sciences Biogeosciences Geochemistry Geology
Content Type	Text
Resource Type	Article
Subject	Earth and Planetary Sciences

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