Methods of intellectual support for decision-making in control systems of programmed mobile radio communication tools

Authors

  • Vladyslav Hol Institute of special communications and information protection at the National technical university of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute”, Kyiv, Ukraine https://orcid.org/0000-0002-9995-9590
  • Serhii Salnyk Institute of special communication and information protection at the National technical university of Ukraine “Igor Sikorsky Kyiv polytechnic institute”, Kyiv, Ukraine https://orcid.org/0000-0003-4463-5705
  • Sergii Ivanchenko Institute of special communication and information protection at the National technical university of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute”, Kyiv, Ukraine https://orcid.org/0000-0003-1850-9596

DOI:

https://doi.org/10.20535/2411-1031.2025.13.2.344714

Keywords:

mobile radio communication, programmable means of communication, management system, decision support, intellectualization

Abstract

The article proposes a method of intelligent decision-making support in control systems of programmable mobile radio communication. In the course of the work, the most common architectures of the management system, types of management system structures, levels of management were considered, an overview of the latest research was conducted, and the relevance of the development of the specified methodology was determined. The process of supporting decision-making in management systems, the process of functioning of the decision-making support system, the list of ways and methods of information technologies that can be used in the functioning of the decision-making support system were also considered. Since modern decision support approaches increase the mathematical complexity of the system, taking into account the goal and requirements for developing the methodology, it is proposed to use a neural network. The essence of the developed methodology is: in the systematization of the process of managing programmable mobile radio communications, the use of initial data that has a connected nature between all the functions of the control system and the characteristic application of programmable mobile radio communications, when using proven mathematical tools to improve indicators of the effectiveness of support decision-making by the control system using neural networks. The proposed technique includes stages that correspond to the sequence of application of appropriate methods and methods in the control system of programmable mobile radio communication devices, namely: data collection and determination of the control goal; construction of a knowledge representation subsystem; classification and clustering of states; selection and application of a neuroalgorithm assessment of conditions; assessment and selection of optimal and alternative solutions; implementation of solutions and their support. The proposed method, thanks to the correct formulation of the research task and the use of a proven mathematical apparatus, allows self-learning of the neural network, taking into account the peculiarities of the functioning of programmed mobile radio communication devices, increasing the speed and accuracy of decision-making based on the intellectualization of decision-making support.

Author Biographies

Vladyslav Hol, Institute of special communications and information protection at the National technical university of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute”, Kyiv

candidate of technical sciences, professor, head of department of security of
state information resources

Serhii Salnyk, Institute of special communication and information protection at the National technical university of Ukraine “Igor Sikorsky Kyiv polytechnic institute”, Kyiv

candidate of technical sciences, senior research fellow scientific research center

Sergii Ivanchenko, Institute of special communication and information protection at the National technical university of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute”, Kyiv

doctor of technical sciences,professor, professor of the department of security of state information resources

References

S. Salnyk, “Methodology of intelligent control of the interaction of control system elements in mobile radio networks”, Information Technology and Security, vol. 10, iss. 2, pp. 241-249, 2022. doi: https://doi.org/10.20535/2411-1031.2022.10.2.270584.

L.N. Berkman, O.V. Barabash, O.M. Tkachenko, A.P. Musienko, O.A. Laptev, and O.V. Svinchuk, “Intelligent control system for infocommunication networks”, Control, navigation and communication systems, vol. 3, iss. 69, pp. 54-59, 2022. doi: https://doi.org/10.26906/SUNZ.2022.3.054.

M.A. Demydenko, Decision Support Systems: tutorial. Dnipropetrovsk, Ukraine: National Mining University, 2016.

O.V. Nesterenko, O.I. Savenkov, and O.O. Falovsky, Intelligent decision support systems: tutorial. Kyiv, Ukraine: Kyiv Nat. Acad. of Management, 2016.

T.A. Zheldak, L.S. Koryashkina, and S.A. Us, Fuzzy sets in control and decision-making systems. Dnipro, Ukraine: NTU “Dnipro Polytechnic”, 2020.

A.O. Cherednichenko, and N.O. Shura, “Application of artificial neural networks as an effective mechanism for making effective management decisions at the enterprise”, Global and National Problems of Economics, vol.4, pp. 628-630, 2015 [Online]. Available: http://global-national.in.ua/archive/4-2015/132.pdf. Accessed on: May 19, 2025.

I.V. Borisov, T.G. Gursky, V.I. Nishchenko, P.V. Khomenko, and Y.V. Tsimura, Modern military means of radio and satellite communication: collection of educational and methodological materials. Kyiv, Ukraine: MITI, 2017. [Online]. Available: https://sprotyvg7.com.ua/wp-content/uploads/2023/07/сучасні.pdf. Accessed on: May 13, 2025.

S.V. Zaitsev, and V.V. Prystyupa, “Study of structural features of distributed programmable wireless systems”, Problems of informatization and management, vol. 2 (42), pp. 34-44, 2013. [Online]. Available: https://jrnl.nau.edu.ua/index.php/PIU/article/view/6469/7203. Accessed on: May 14, 2025.

J.G. Fernando, and M. Baldelovar, “Decision Support System: Overview, Different Types and Elements”, Technoarete Transactions on Intelligent Data Mining and Knowledge Discovery, vol. 2 (2), pp. 13-18, 2022. doi: https://doi.org/10.36647/TTIDMKD/02.02.A003.

H. Taherdoost, and M. Madanchian, “Decision Making: Models, Processes, Techniques”, Cloud Computing and Data Science, vol. 5, iss. 1, 14 p. 2023. doi: https://doi.org/10.37256/ccds.5120233284.

O.O. Marchenko, and T.V. Rossada, Current Problems of Data Mining: tutorial. Kyiv, Ukraine: Taras Shevchenko Nat. Un. of Kyiv, 2017. [Online]. Available: http://csc.knu.ua/media/filer_public/38/03/3803002b-e068-4a08-8a6c-a4edc183892a/datamining20170917.pdf. Accessed on: May 14, 2025.

S.V. Salnyk, and O.S. Salii, “Methodology of classification of critical data parameters in control systems of unmanned aerial vehicles using neural networks”, Collection of scientific works of Kharkiv Nat. Un. of Air Force, vol. 2 (80), pp. 83-92, 2024. doi: https://doi.org/10.30748/zhups.2024.80.11.

H.A. Darbi, and E.M. Saleh, “Decision Support System: Analysis and Design Methodology”, in Proc 2nd Int. Maghreb Meet. of the Conf. on Sci. and Tech. of Aut. Contr. and Comp. Eng. (MI-STA), Sabratha, Libya, 2022, pp. 260-266. doi: https://doi.org/10.1109/MI-STA54861.2022.9837769.

Published

2025-11-27

How to Cite

Hol, V., Salnyk, S., & Ivanchenko, S. (2025). Methods of intellectual support for decision-making in control systems of programmed mobile radio communication tools. Collection "Information Technology and Security", 13(2), 290–299. https://doi.org/10.20535/2411-1031.2025.13.2.344714

Issue

Section

ARTIFICIAL INTELLIGENCE IN THE CYBERSECURITY FIELD