Fuzzy-Based Clustering of Epicenters and Strong Earthquake-Prone Areas

An original Discrete Perfect Sets (DPS) algorithm was developed and applied to clustering of earthquake epicenters with M≥3.0 in California.The obtained clusters correspond well with the locations of the epicenters of strong earthquakes with M≥6.5.This fact allows considering them as earthquake-prone areas for the magnitude M≥6.5.We compared the obtained clusters with the areas recognized in 1976 using Earthquake-Prone Areas (EPA) method.The comparison shows that the epicenter clusters recognized by DPS algorithm are mostly located within the EPA areas or continue them in a specific direction.At the same time, the clusters cover significantly smaller zones, about 13% of the total area of the EPA zones.An important feature of the performed DPS clustering is that it uses only earthquake epicenters data instead of a wide range of geophysical, geomorphological and geological objects and parameters used by EPA technique.The efficiency of DPS clustering for recognition of earthquake-prone areas is also illustrated by applying to the seismic region of Caucasus.