Научный журнал Моделирование, оптимизация и информационные технологииThe scientific journal Modeling, Optimization and Information Technology
cетевое издание
issn 2310-6018

Algorithms for cluster-identification of emergency situations in the management of technogenic and fire safety processes

idOrlova D. Fursov, I.   Kuprienko P.  

UDC УДК 004.514
DOI: 10.26102/2310-6018/2021.33.2.020

  • Abstract
  • List of references
  • About authors

The problem of cluster-identification of emergency situations in the management of the processes of ensuring technogenic and fire safety is considered. The assignment of a situation to a class is carried out by comparing it with typical elements of different classes and selecting the nearest one. To do this, a measure of class proximity is introduced, which depends on the form in which the signs of situations are set. In the case where these features are expressed in deterministic quantities, the square of the Euclidean distance between the vectors of feature values is used as a measure of the proximity of situations (the smaller the distance, the closer the situations are). The corresponding definition of the features of a typical situation is the arithmetic mean of the features in the sample representing the class of the situation. When the features are set by probabilistic values, the measure of proximity is the generalized probability of identifying threatening, critical, and catastrophic situations. In the case when the signs of a situation are set on conceptual scales, it is proposed to use the apparatus of semantic networks to solve the problem, and the process of identifying situations is understood as a multi-step process that includes: a) conceptualization of the problem; b) generation of solution options; c) evaluation and ranking of solutions; d) selection of the preferred solution. This understanding of the process of identifying situations most fully reflects the structure of human intellectual activity and allows us to proceed to the formalization of these operations based on the use of the apparatus of semantic networks.

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Orlova Darya of the Institute of the Federal Penitentiary Service of

Email: dasha_scorobogat@mail.ru

ORCID |

Voronezh Institute of the Federal Penitentiary Service of Russia

Voronezh, Russia

Fursov, Ilya

Email: cva57@yandex.ru

Voronezh State Technical University

Voronezh, Russia

Kuprienko Pavel
doctor of Technical Sciences associate Professor

Voronezh State Technical University

Voronezh, Russia

Keywords: technogenic and fire safety, emergency, cluster-identification, feature, algorithm

For citation: Orlova D. Fursov, I. Kuprienko P. Algorithms for cluster-identification of emergency situations in the management of technogenic and fire safety processes. Modeling, Optimization and Information Technology. 2021;9(2). Available from: https://moitvivt.ru/ru/journal/pdf?id=985 DOI: 10.26102/2310-6018/2021.33.2.020 (In Russ).

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Revised 26.07.2021

Accepted 30.07.2021

Published 02.08.2021