Abstract:
This paper addresses the issues related to controlling and preventing anthropogenic emergencies. The early detection of critical conditions, the accuracy, and reliability of monitoring system parameters is the key to the prevention of anthropogenic catastrophes of different levels.
A model of the emergency as a fuzzy situation has been proposed, based on the theory of fuzzy sets and the concept of a linguistic variable; a set of indicators has been determined that fully describe the factors affecting emergency. The set of indicators is a combination of both quantitative and qualitative data. It has been shown that the proposed fuzzy model is consistent with the characteristics and conditions of emergency occurrence at the objects of critical infrastructure and, at the same time, makes it possible to process both quantitative and qualitative indicators. This approach enables using fuzzy relations to form the similarity groups and to build rule bases in the decision support systems taking into consideration the similarity of situations, which improves the effectiveness of decision support systems.
Under extreme conditions, prompt and qualified managerial decision making is the most important task, which is solved, in particular, by the decision support systems. Since the construction of a rule base for an intelligent system requires the participation of experts, this paper has proposed a method for representing and processing expert data, which makes it possible to define the characteristics of their consistency and to choose the appropriate processing method. The proposed approaches to modeling emergencies could make it possible to detect situations in order to control and prevent them and to devise a set of activities in the case of an emergency, which would save human life and natural resources.
