Spatial clustering of seismic events analysis using the Discrete Perfect Sets (DPS)algorithm: Pribaikalye

The study aims to get new insights in the evolving clustering of seismicity to be the preconditions for the further effective use of the improved SHA technique in earthquake-prone regions. Discrete Mathematical Analysis DMA (Gvishiani et al. 2008; Agayan et al. 2018) is a series of algorithms for analyzing discrete data, united by a common formal basis, which is fuzzy models of discrete analogs of the fundamental concepts of classical mathematical analysis: limits, continuity, smoothness, connectivity, monotonicity, extremum, etc. In this study, the use of DMA is associated with clustering: it has to select clusters of discrete observations according to a given criterion (classification of discrete observations belonging to one of the clusters) (Gordon, 1981). The results of application of the Discrete Perfect Sets DPS topological filtering algorithm to seismic events in the Baikal area are presented. For the purpose of our analysis, we consider the Baikal Division of the Geophysical Survey, Federal Research Center of the Russian Academy of Sciences, BDRGS (2020) catalogue data. Specifically the epicenters for magnitudes equal to or more than 2.6 (energy class K≥8.6, accepted in catalogue homepage) for the period 1989–2018 within 48–58°N and 99–122°E. The study was carried out as part of the Russian Federation State task of Scientific Research Works on "Seismic hazard assessment, development and testing of earthquake prediction methods"(No. 0143-2019-0006).