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Cognitive and Information Decision Support Technologies for Operational Management of Energy-Active Objects in Boundary Modes

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Lecture Notes in Data Engineering, Computational Intelligence, and Decision Making (ISDMCI 2022)

Abstract

The article considers the activity of the operator in emergency situations. It is proved that the implementation of perception of situations (building an image of the situation in terminal time on the basis of intelligent processing of data streams) in the control process in a hierarchical automated control system depends, on the one hand, on the intellectual level of the operator, and on the other hand - on his professional training, knowledgeable training and multimedia presentation tools. The article also considers the operator’s ability to perceive scenarios and images of events (based on the processing of data streams), to identify signs of criticality of modes and factors of influence on both the technological system and decision-making (to ensure minimization of risk situations). The most complex component of this process is the perception (as a whole) by the person-operator of a set of automated control system of technological processes structures (projecting 3D image). Such an image should represent physical and chemical-technological energy-active processes in their interconnection, representation of these actions in the cognitive structure of the operator’s thinking (in the form of scenario configurations trends), their evaluation when making control decisions. On the basis of the conducted research, the requirements for efficient decision-making were formulated. An analysis of the problem of assessing the operator’s intellectual abilities was carried out. The functional structure of the purpose-directed activity process and the scheme of control tasks in conditions of the risk of accidents (which leads to the release of toxic waste into the environment) is given.

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Correspondence to Yuliya Miyushkovych .

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Sikora, L., Lysa, N., Martsyshyn, R., Miyushkovych, Y. (2023). Cognitive and Information Decision Support Technologies for Operational Management of Energy-Active Objects in Boundary Modes. In: Babichev, S., Lytvynenko, V. (eds) Lecture Notes in Data Engineering, Computational Intelligence, and Decision Making. ISDMCI 2022. Lecture Notes on Data Engineering and Communications Technologies, vol 149. Springer, Cham. https://doi.org/10.1007/978-3-031-16203-9_21

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