Modeling the threats of dangerous weather conditions using the theory of blurred sets

Abstract

Introduction. The author's methods of forecasting the threat of emergencies caused by hazardous meteorological conditions are considered to ensure the required level of safety, including on the territory of the Republic of Crimea. Research objective: increasing the efficiency of the warning system and informing the population about emergency situations caused by hazardous weather conditions. Methods. To solve the problem of decision-making when predicting emergency situations caused by hazardous meteorological conditions, the methods of the theory of fuzzy sets are used. The article presents a method for determining the criteria, with the help of which it is possible to establish exactly whether the presented object belongs to the corresponding class. To implement the goal of timely informing and alerting the population and services of the Unified State System for the Prevention and Response of Emergencies (RSChS), lowering the entropy of an adequate assessment of the situation and taking effective measures to preserve the life and health of people, it is proposed to rank the criteria by wind speed, precipitation and air temperature , according to the levels of danger, indicating specific preventive measures for the population, management bodies and RSChS services. Results and discussion. A method is presented for determining the criteria by which it is possible to establish exactly whether the presented object belongs to the appropriate class. The method allows you to determine to what level of danger the situation can go. Conclusions. As the analysis has shown, the likelihood of the occurrence of a yellow level of threat during the year is practically the same. At the same time, the likelihood of a deterioration in the situation with the already emerging yellow threat level in the autumn-winter period is slightly higher. When the wind speed reaches the upper boundaries of the yellow level of threat in the autumn-winter period, the situation worsens twice as often than with the same values of the indicators in the spring-summer period. Key words: meteorological conditions, forecasting, fuzzy set theory, decision support system.