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| Titel |
A tri-stage cluster identification model for accurate analysis of seismic catalogs |
| VerfasserIn |
S. J. Nanda, K. F. Tiampo, G. Panda, L. Mansinha, N. Cho, A. Mignan |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1023-5809
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| Digitales Dokument |
URL |
| Erschienen |
In: Nonlinear Processes in Geophysics ; 20, no. 1 ; Nr. 20, no. 1 (2013-02-18), S.143-162 |
| Datensatznummer |
250017736
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| Publikation (Nr.) |
 copernicus.org/npg-20-143-2013.pdf |
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| Zusammenfassung |
| In this paper we propose a tri-stage cluster identification model that is a
combination of a simple single iteration distance algorithm and an iterative
K-means algorithm. In this study of earthquake seismicity, the model
considers event location, time and magnitude information from earthquake
catalog data to efficiently classify events as either background or mainshock
and aftershock sequences. Tests on a synthetic seismicity catalog demonstrate
the efficiency of the proposed model in terms of accuracy percentage
(94.81% for background and 89.46% for aftershocks). The close agreement
between lambda and cumulative plots for the ideal synthetic catalog and that
generated by the proposed model also supports the accuracy of the proposed
technique. There is flexibility in the model design to allow for proper
selection of location and magnitude ranges, depending upon the nature of the
mainshocks present in the catalog. The effectiveness of the proposed model
also is evaluated by the classification of events in three historic catalogs:
California, Japan and Indonesia. As expected, for both synthetic and historic
catalog analysis it is observed that the density of events classified as
background is almost uniform throughout the region, whereas the density of
aftershock events are higher near the mainshocks. |
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