Methodology of geodynamic zoning based on factor analysis of spatial data

The article considers a geodynamic zoning methodology based on the factor analysis of spatial data. This algorithm includes several key principles: identification of geodynamic factors, data collection and processing, statistical analysis, territory classification and forecasting. Based on application of modern methods of data analysis, including the use of neural networks, this methodology allows us to determine the importance of each geodynamic factor. The article discusses the problem of selecting and evaluating the efficiency of factor selection in geodynamic zoning of territories. A special attention is paid to identification of informative signs and overcoming the problem of retraining. An algorithm for analyzing the frequency of repetition is presented to assess the distribution uniformity of the generalizing function Фkn (F) values. The importance of this method is emphasized for ensuring the safety of mining operations in hazardous fields and managing geodynamic risks. Identification of such zones makes it possible to efficiently concentrate efforts and resources on preventing accidents and minimizing risks, thus safeguarding the worker and reducing the chances of unexpected emergencies in the course of field operations.