This paper presents a decision support model for responding to forest fires in mountainous areas using fuzzy logic. The research methods include the Mamdani method for constructing a fuzzy inference system, the use of linguistic variables to describe environmental conditions and risk factors, and the formation of a rule base based on expert knowledge. The developed model implements the principles of situational management and enables determination of the fire danger level, selection of extinguishing methods, response tactics, and optimal resource allocation. Its practical significance lies in the potential application of the model in decision support systems of the Russian Ministry of Emergency Situations for operational planning and forecasting during forest fire suppression in challenging mountainous conditions.

Keywords: forest fires, mountainous terrain, fuzzy logic, decision support, intelligent systems, situational management

The article is devoted to applied issues of improving regional security management processes through the development of methods for analyzing data on emergency situations. In order to identify patterns in the occurrence of emergency situations, multidimensional methods of processing statistical data were used. A multidimensional classification of data in the field of emergency situations based on fuzzy logic is proposed. The classification was performed using a fuzzy inference system with clear membership functions. As statistical data, data on emergency situations of a man-made, natural and biological-social nature that occurred in the federal districts of Russia in 2020, including data on dead and saved people, were considered. An analysis of data samples on regional emergency situations was carried out according to 5 criteria, and clustering of regions was carried out.

Keywords: emergency situations, fuzzy multidimensional clustering, fuzzy logic, fuzzy inference system, computer program, mathematical model, forecasting, decision making