Problem statement. When modeling a complex technical system, the issues of parameter estimation are of primary importance. To solve this problem, it is necessary to obtain a methodology that allows eliminating errors and inaccuracies in obtaining numerical parameters. Goal. The article is devoted to a systematic analysis of the methodology for estimating the parameters of a complex technical system using the interval estimation method. The research method. A systematic analysis of the methods of using interval estimates of numerical parameters is carried out. The decomposition and structuring of the methods were carried out. Results. The expediency of using a methodology for describing the parameters of a complex technical system using the interval estimation method is shown. An analysis of the use of various interval estimation models is presented. Practical significance. Application in the analysis and construction of complex systems is considered as a practical application option. The method of estimating the parameters of a complex technical system using the interval estimation method can be used as a practical guide.

Keywords: interval estimation, parameter estimation, numerical data, fuzzy data, complex technical systems

The article considers issues related to making management decisions when ensuring safety in emergency situations. It reflects the features of making management decisions in emergency situations, when achieving a guaranteed level of safety is not always possible. The control loop is presented and the connections between the elements of the first and second stages are analyzed. It is shown that uncertainty in making management decisions arises due to a lack of information about the control object or is caused by unprofessional actions of the decision maker. It is proposed to create and use in practice a digital twin of safety in an emergency situation to eliminate uncertainties in making management decisions. Decomposition of the task into subtasks allows for the process of collecting and analyzing aggregate information about the control object to eliminate uncertainties and minimize risks in the development, adoption and implementation of management decisions in an emergency situation when ensuring safety.

Keywords: control model, control loop, uncertainty, risk, digital twin, decomposition, emergency safety