Typification of the development of dangerous situations for the response of operational services in territories based on the analysis of many years of statistics

The article formulates a complex problem of modeling and forecasting the development of dangerous processes that are formed in the most diverse areas of modern society's life. Solving this problem is relevant and significant for the effective functioning of emergency response services in making management decisions, which, in turn, helps to accelerate the elimination of emergencies and minimize human casualties and economic losses. Two approaches to solving this problem are presented in relation to the response of operational services. Both approaches are based on the analysis of dynamic series. A risk typology of the territories of the Russian Federation has been performed based on the quantitative analysis of the trend and seasonal components of the dynamic series of the number of emergencies that occurred between 2009 and 2021. It has been shown that the trend components determine the main trend of changes in the number of emergencies over time, while the seasonal component characterizes the variability of regular changes in their dynamics. The article highlights the federal districts where similar scenarios of emergency situation dynamics are formed. It discusses the issues of modeling the dynamics of phishing attacks in the cyberspace of the Russian Federation and solves the problem of obtaining predictive information about the number of such attacks. The article examines the structure of the dynamic series of phishing attacks to identify its trend, seasonal, and random components. The article uses a neural LSTM model for predicting phishing attacks. The error in the forecast obtained with its help is on average no more than 6 %. It is concluded that recurrent neural networks can be useful in the study of other types of cybercrimes. The materials of the article and the approaches developed in it are scientifically significant for the further development of a system of forecasting models that allow for the study of complex interactions in the implementation of dangerous phenomena in the modern territorial and information-telecommunication spaces of the Russian Federation, as well as for the analytical services of the Ministry of Emergency Situations and the Ministry of Internal Affairs.

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