ИСТИНА

The Topological Filtering Algorithm, Discrete Perfect Set (DPS) by Agayan et al. (2018), was developed within the framework of discrete mathematical analysis, which involves fuzzy models of discrete analogs of fundamental concepts of classical mathematical analysis. It is designed to select clusters of discrete observations according to a given criterion (classification of discrete observations belonging to one of the clusters) (Gordon, 1981). In this study, we applied the iterative S-DPS modification of the DPS algorithm (Agayan et al., 2022) for the sequential extraction of linear structures from an initial array of point objects. Specifically, we considered the catalogue data from the Baikal Division of the Geophysical Survey, Federal Research Center of the Russian Academy of Sciences, as the initial set of point objects. In each iteration, the densifications identified by S-DPS can be interpreted as discontinuous disturbances of various ranks. With each iteration, weaker yet significant concentrations are discerned. The identification of these discontinuous disturbances as linear structures, and their interpretation were conducted using an expert, non-automated approach. Derived from expert analysis of a few sequential iterations of the S-DPS algorithm, this facilitated the identification of potential seismogenic structures for two selected territories in the Lake Baikal region. For both territories, the obtained structures were compared with the mapped active faults in the Lake Baikal region (Active Faults of Eurasia Database, Zelenin et al., 2022). The iterative application of the S-DPS algorithm, combined with expert linear structures analysis, provides a nuanced approach to understanding the complexities of seismogenic features and their potential seismic implications. This methodology offers significant potential for analysing regional seismicity, aiming to discover new or adjust already mapped seismogenic structures.