Cluster Analysis, Data Mining, Multi dimensional Visualization of Earthquakes英文电子书.pdf

Cluster Analysis, Data-Mining, Multi-dimensional Visualization of Earthquakes over Space, Time and Feature Space 1 2 Witold Dzwinel , David A.Yuen , 1,2 3 4 5 Krzysztof Boryczko , Yehuda Ben-Zion , Shoichi Yoshioka , Takeo Ito 1 AGH Institute of Computer Science, al. Mickiewicza 30, 30-059, Kraków, Poland 2 Minnesota Supercomputing Institute, Univ. of Minnesota, Minneapolis, MN 55455, USA 3Department of Earth Sciences, University of Southern California, Los Angeles, CA 98809, USA 4 Dept. of Earth and Planteary Sciences, Kyushu University, Fukuoka, 812-8581, Japan 5 Graduate School of Environmental Studies, Nagoya, University, Furo -cho, Nagoya , Aichi, 464-8602, Japan Abstract A novel technique based on cluster analysis of the multi-resolutional structure of earthquake patterns is developed and applied to observed and synthetic seismic catalogs . The observed data represent seismic activities situated around the Japanese islands in the 1997-2003 time interval. The synthetic data were generated by numerical simulations for various cases of a heterogeneous fault governed by 3-D elastic dislocation and power-law creep. At the highest resolution , we analyze the local cluster structure in the data space of seismic events for the two types of catalogs by using an agglomerative clustering algorithm. We demonstrate that small magnitude events produce local spatio-temporal patches