Abstract—Custering of seismic events is a distinctive feature of the Baikal Rift Zone. Such a common spatial location of earthquake sources suggests regularities in the development of seismic activity in the areas of their clustering, which may be related to the physical properties of the environment. The most significant geophysical characteristics describing physical fields include the seismic wave propagation velocities, resistivity, and temperature. The paper considers clustering of each of the listed geophysical parameters as well as their combination using the Kohonen neural network. The identified clusters are compared with data of seismic events in the area under consideration. This method allows studying the contribution and comparative informativeness of the geophysical characteristics of the environment to the formation of a zone of weakness of the crust. Integrated analysis of geophysical data using Kohonen self-organizing maps allowed us to find a set of the most informative geophysical parameters and their values, which turned out to be resistivity and temperature. The integration of these parameters revealed a spatial correlation with the accumulation of seismic events in the area of the Mishikha depression of the South Baikal Basin of Lake Baikal.
Popova et al. (2026) studied this question.