Information System Functioning Based on Multidimensional Time Series

Authors

DOI:

https://doi.org/10.18372/1990-5548.88.20967

Keywords:

data processing, information systems, mathematical model, multivariate time series, system state, temporal dependencies

Abstract

The paper addresses the problem of mathematical modeling of complex information systems characterized by a large number of interrelated parameters and heterogeneous information flows. Such systems demonstrate a dynamic behavior over time, which requires the application of methods capable of analyzing temporal dependencies between system parameters. A mathematical model of complex information system functioning based on multivariate time series is proposed. The developed model allows formalizing the processes of system state evolution and capturing relationships between different information streams. In the proposed approach, the system state is represented as a vector time process that includes multiple parameters describing various aspects of the system operation. The mathematical framework of the model describes the dynamics of system state formation and evolution while taking into account external influences and stochastic disturbances. The proposed approach enables a consistent analysis of multidimensional data and allows investigating patterns in the functioning of information systems in dynamic environments. Simulation experiments demonstrate the applicability of the proposed model for analyzing the behavior of complex information systems and evaluating their states based on temporal relationships between system parameters. The obtained results can be applied in the development of methods for processing multidimensional data and designing decision support systems for managing complex information processes.

Author Biographies

Olena Nechyporuk , State University "Kyiv Aviation Institute"

Doctor of Engineering

Professor

Department of Intelligent Cybernetic Systems

Serhii Podelskyi , State University "Kyiv Aviation Institute"

Postgraduate Student

Department of Intelligent Cybernetic Systems

References

S. O. Kashkevich, (Ed.) Decision support systems: mathematical support, p. 202, 2025, Kharkiv: TECHNOLOGY CENTER PC. https://doi.org/10.15587/978-617-8360-13-9

H. A. Pliekhova, S. M. Neronov, M. V. Kostikova, & S. O. Kashkevich, “Improvement of the secure routing model in software-defined networks,” Bionics of Intelligence (Kharkiv National University of Radio Electronics), (1), 50–57, 2024. https://doi.org/10.30837/bi.2024.1(100).07

K. A. Tamer, O. Sova, O. Shaposhnikova, V. Yashchenok, I. Stanovska, S. Shostak, O. Rudenko, S. Petruk, O. Matsyi, & S. Kashkevich, “Development of a solution search method using a combined bio-inspired algorithm,” Eastern-European Journal of Enterprise Technologies, 1(4/127), 6–13, 2024. https://doi.org/10.15587/1729-4061.2024.298205.

B. A. Mohammed, I. Stanovska, S. Kashkevich, A. Lebedynskyi, Y. Vakulenko, N. Protas, O. Klyuchak, O. Lastivka, A. Semeniuk, and O. Kivshar, “Development of a methodological approach for assessing the condition of complex organizational and technical systems,” Eastern-European Journal of Enterprise Technologies, 2 (3 (134)), 47–53, 2025. https://doi.org/10.15587/1729-4061.2025.326468.

V. Koval, O. Nechyporuk, A. Shyshatskyi, et al., “Development of a method of complex analysis and multidimensional forecasting of the state of intelligence objects,” Eastern-european Journal of Enterprise Technologies, рр. 31−41, 2023. https://doi.org/10.15587/1729-4061.2023.276168.

O. Tachinina, O. Lysenko, S. Ponomarenko, S. Chumachenko, and V. Kutiepov, “Engineering Methodology for the Synthesis of Control Algorithms for Digital Electric Drives of Mechatronic Devices of Flying Search Robots,” Lecture Notes in Networks and Systems Open source preview, 2024, 996 LNNS, 427–439.

O. Lysenko, O. Tachinina, I. Alekseeva, Y. Tymofelev, “Engineering Method for Adjusting Electric Drive Regulators of Manipulator Motion Units With Significant Nonlinearities,” ICST-2025: Information Control Systems & Technologies, September 24-26, 2025, Odesa, Ukraine, Ceur Workshop ProceedingsOpen source preview, 2025, 81–93.

O. Poliarus, S. Krepych, & I. Spivak, “Hybrid approach for data filtering and machine learning inside content management system,” Advanced Information Systems, 7(4), 70–74, 2023. https://doi.org/10.20998/2522-9052.2023.4. 14–32.

M. S. Braik, “Chameleon swarm algorithm: a bio-inspired optimizer for solving engineering design problems,” Expert Systems with Applications, vol. 174, 114685, 2021. https://doi.org/10.1016/j.eswa.2021.114685.

S. Kashkevich, I. Dmytriiev, I. Shevchenko, O. Lytvynenko, L. Shabanova-Kushnarenko, and N. Apenko, Scientific-method apparatus for improving the efficiency of information processing using artificial intelligence, Information and control systems: modelling and optimizations: collective monograph. Kharkiv: ТЕСHNOLOGY СЕNTЕR PC, 2024, рр. 137–167. https://doi.org/10.15587/978-617-8360-04-7.ch5.

B. A. Mohammed, I. Stanovska, S. Kashkevich, A. Lebedynskyi, Y. Vakulenko, N. Protas, O. Klyuchak, O. Lastivka, A. Semeniuk, and O. Kivshar, “Development of a methodological approach for assessing the condition of complex organizational and technical systems,” Eastern-European Journal of Enterprise Technologies, 2 (3 (134)), 47–53, 2025. https://doi.org/10.15587/1729-4061.2025.326468.

C. Pozna, R. -E. Precup, E. Horváth and E. M. Petriu, “Hybrid Particle Filter–Particle Swarm Optimization Algorithm and Application to Fuzzy Controlled Servo Systems,” IEEE Transactions on Fuzzy Systems, vol. 30, no. 10, pp. 4286−4297, Oct. 2022. https://doi.org/10.1109/TFUZZ.2022.3146986.

N. Paliwal, L. Srivastava, and M. Pandit, Application of grey wolf optimization algorithm for load frequency control in multi-source single area power system,” Evolutionary Intelligence, vol. 15, pp. 563–584, 2022. https://doi.org/10.1007/s12065-020-00530-5.

H. Khudov, I. Khizhnyak, S. Glukhov, N. Shamrai, & V. Pavlii, “The method for objects detection on satellite imagery based on the firefly algorithm,” Advanced Information Systems, vol. 8, no. 1, pp. 5–11, 2024. https://doi.org/10.20998/2522-9052.2024.1.01.

S. R. Owaid, Y. Zhuravskyi, O. Lytvynenko, A. Veretnov, D. Sokolovskyi, G. Plekhova, V. Hrinkov, T. Pluhina, S. Neronov, & O. Dovbenko, “Development of a method of increasing the efficiency of decision-making in organizational and technical systems,” Eastern-European Journal of Enterprise Technologies, vol. 1, no.4 (127), pp. 14–22, 2024. https://doi.org/10.15587/1729-4061.2024.298568.

V. Tyurin, R. Bieliakov, E. Odarushchenko, V. Yashchenok, O. Shaposhnikova, A. Lyashenko, O. Stanovskyi, B. Melnyk, S. Sus, & M. Dvorskyi, “Development of a solution search method using an improved locust swarm algorithm,” Eastern-European Journal of Enterprise Technologies, vol. 5, no. 4 (125), pp. 25–33, 2023. https://doi.org/10.15587/1729-4061.2023.287316.

S. Yakymiak, Y. Vdovytskyi, Y. Artabaiev, L. Degtyareva, Y. Vakulenko, S. Nevhad, V. Andronov, R. Lazuta, P. Shapoval, & Y. Artamonov, “Development of the solution search method using the population algorithm of global search optimization,” Eastern-European Journal of Enterprise Technologies, vol. 3, no. 4 (123), pp. 39–46, 2023. https://doi.org/10.15587/1729-4061.2023.281007.

B. A. Mohammed, O. Zhuk, R. Vozniak, I. Borysov, V. Petrozhalko, I. Davydov, O. Borysov, O. Yefymenko, N. Protas, & S. Kashkevich, “Improvement of the solution search method based on the cuckoo algorithm,” Eastern-European Journal of Enterprise Technologies, vol. 2, no. 4 (122), pp. 23–30, 2023. https://doi.org/10.15587/1729-4061.2023.277608.

L. Raskin, L. Sukhomlyn, D. Sokolov, & V. Vlasenko, “Multi-criteria evaluation of the multifactor stochastic systems effectiveness,” Advanced Information Systems, vol. 7, no. 2, pp. 63–67, 2023. https://doi.org/10.20998/2522-9052.2023.2.09.

S. Arora and S. Singh, “Butterfly optimization algorithm: a novel approach for global optimization,” Soft Computing, vol. 3, pp. 715–734, 2019. https://doi.org/10.1007/s00500-018-3102-4

Downloads

Published

2026-04-18

How to Cite

Nechyporuk , O., & Podelskyi , S. (2026). Information System Functioning Based on Multidimensional Time Series. Electronics and Control Systems, 2(88), 61–68. https://doi.org/10.18372/1990-5548.88.20967

Issue

Vol. 2 No. 88 (2026)

Section

INFORMATION SYSTEMS AND TECHNOLOGIES

License

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

The scientific journal “Electronics and control systems” adheres to the principles of Open Access and provides free, immediate, and permanent access to all published materials without financial, technical, or legal barriers for readers.

All articles are published in Open Access under the Creative Commons Attribution 4.0 International (CC BY 4.0) license.

Copyright

Authors who publish their works in the journal “Electronics and control systems”:

  • retain the copyright to their publications;

  • grant the journal the right of first publication of the article;

  • agree to the distribution of their materials under the CC BY 4.0 license;

  • have the right to reuse, archive, and distribute their works (including in institutional and subject repositories), provided that proper reference is made to the original publication in the journal.