Scenario approach in the management of monitoring processes in natural-technical systems

A.V. Skatkov, Yu.V. Doronina, A.A. Bryukhovetskiy

 Federal State Educational Institution of Higher Education «Sevastopol State University», RF, Sevastopol, Universitetskaya St., 33

E-mail: YVDoronina@sevsu.ru

DOI: 10.33075/2220-5861-2023-1-108-117

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Mathematical models and methods of multilevel optimization of structural synthesis of UMV information exchange channels for environmental control systems

D.V. Moiseev, A.V. Skatkov, A.A. Bryukhovetskiy

 Sevastopol State University, RF, Sevastopol, Universitetskaya St., 33

E-mail: dmitriymoiseev@mail.ru

DOI: 10.33075/2220-5861-2022-4-133-142

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Collaborative strategies for detecting interface vulnerabilities of information and measurement networks of NTS with 5G technologies  

A.V. Skatkov, A.A. Bryukhovetskiy

 Federal State Educational Institution of Higher Education «Sevastopol State University», RF, Sevastopol, Universitetskaya St., 33

E-mail: a.alexir@mail.ru

DOI: 10.33075/2220-5861-2022-3-84-96

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Swarm intelligence in the problems of detecting anomalies and states of natural-technical systems and objects

A.V. Skatkov, A.A. Bryukhovetskiy, D.V. Moiseev, I. A. Skatkov

 Sevastopol State University, RF, Sevastopol, Universitetskaya St., 33

E-mail: dmitriymoiseev@mail.ru

DOI: 10.33075/2220-5861-2021-3-119-126

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Software and hardware module to support decision-making of qualitative abnormal changes presence in sample data based on information metrics

Y.E. Shishkin1, A.V. Skatkov2

 1Institute of Natural and Technical Systems, RF, Sevastopol, Lenin St., 28

2Sevastopol State University, RF, Sevastopol, Universitetskaya St., 33

E-mail: iurii.e.shishkin@gmail.com

DOI: 10.33075/2220-5861-2021-2-142-151

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Multivariate multichannel software and measurement complex for detecting anomalous states of natural and technical objects and systems

A.V. Skatkov, A.A. Bryukhovetskiy, D.V. Moiseev

Sevastopol State University, RF, Sevastopol, Universitetskaya St., 33

E-mail: dmitriymoiseev@mail.ru

DOI: 10.33075/2220-5861-2021-2-119-130

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