Selecting primary sensor types considering nonlinear error characteristics

Y.E. Shishkin, A.V. Skatkov Institute of Natural and Technical Systems, RF, Sevastopol, Lenin St., 28 E-mail: iurii.e.shishkin@gmail.com DOI: 10.33075/2220-5861-2023-4-112-123  UDC 681.3       EDN: https://elibrary.ru/speyxa Abstract: The paper addresses the application of simulation modeling and mathematical methods to assist decision-making in selecting the type of primary sensor, considering its non-linear error characteristics. The approach integrates algorithmic solutions … Read more

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Conditions vulnerability identification of natural and technical objects based on linear spline interpolation of interface traffic intensity

A.V. Skatkov, A.A. Bryukhovetskiy, I.А. Skatkov

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

a.alexir@mail.ru

DOI: 10.33075/2220-5861-2021-4-143-151

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Investigation of a model of probabilistic automata for detecting changes in the state of resources of autonomous measurement systems

A.V. Skatkov, A.A. Bryukhovetsky, D.V. Moiseev

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

E-mail: dmitriymoiseev@mail.ru

DOI: 10.33075/2220-5861-2020-4-58-64

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Increasing the operability of environmental monitoring by data mining of info-communication processes

V.P. Evstigneev,  D.Yu. Voronin,  A.V. Skatkov,  Yu.V.Tacyi

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

Email: vald_e@rambler.ru

DOI: 10.33075/2220-5861-2019-4-54-59

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Discriminant approach to detect anomalies using Markov sequences

A.V. Skatkov, A.A. Bryukhovetskiy, D.V. Moiseev, Yu.E. Shishkin

 1Sevastopol State University, RF, Sevastopol, Universitetskaya St., 33

Email: dmitriymoiseev@mail.ru

2Institute of Natural and Technical Systems, RF, Sevastopol, Lenin St., 28

DOI: 10.33075/2220-5861-2019-4-43-49

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 Kullbak measure in problems of dynamic clustering of observations of the environmental state

A.V. Skatkov1, A.A. Bryukhovetskiy1, D.V. Moiseev1, Iu.E. Shishkin1,2

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

2 Institute of Natural and Technical Systems, Russian Federation, Sevastopol, Lenin St., 28

E-mail: dmitriymoiseev@mail.ru

DOI: 10.33075/2220-5861-2019-3-35-38

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Intelligent system for adaptive selection of scenarios for parametric monitoring data divergence detection

 Y.E. Shishkin1,2, A.V. Skatkov1

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

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

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

DOI: 10.33075/2220-5861-2019-2-37-42

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Increasing the reliability of risk assessments in the monitoring processes described by general distributions

 Y.E. Shishkin1,2, A.V. Skatkov1

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

2 Institute of Natural and Technical Systems, Russian Federation, Sevastopol, Lenin St., 28

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

DOI: 10.33075/2220-5861-2019-1-41-47

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