Model for Integrating Different Types of Data in Multilevel Information Structures

Authors

DOI:

https://doi.org/10.18372/1990-5548.88.20968

Keywords:

information system, mathematical model, data fusion, multisource data integration, information processing model, heterogeneous information streams

Abstract

This article examines the problem of integrating heterogeneous data within multi-level information structures operating under conditions of heterogeneous data sources and variable dynamics of information flows. The relevance of this research stems from the growing volume of data, the diversity of formats, and the need to establish a harmonised information representation for further analysis. The aim of the work is to develop a mathematical model for the integration of heterogeneous data, which formalises the processes of harmonising information flows of different nature. The paper analyses the characteristics of information flow formation and identifies factors influencing the effectiveness of data integration, in particular varying arrival rates, noise levels and source reliability. A multi-level integration model is proposed, which includes stages of pre-processing, normalisation, harmonisation and the formation of an integrated representation. The results obtained showed that the use of a multi-level approach allows for improved consistency of information flows and a reduction in the impact of noise and uncertainty. The proposed model can be used in data processing and decision support systems within complex information environments.

Author Biographies

Svitlana Kashkevych , State University Kyiv Aviation Institute

Senior Lecturer

Department of Intelligent Cybernetic Systems 

Oleksandr Lastivka , State University “Kyiv Aviation Institute”

Postgraduate Student

Department of Intelligent Cybernetic Systems 

References

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

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.

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.

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

https://doi.org/10.15587/1729-4061.2025.326468.

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.

A. Zuev, D. Karaman, and A. Olshevskiy, “Wireless sensor synchronization method for monitoring short-term events”, Advanced Information Systems, vol. 7, no. 4, pp. 33–40, 2023. https://doi.org/10.20998/2522-9052.2023.4.04

H. Kuchuk and E. Malokhvii, “Integration of IOT with Cloud, Fog, and Edge Computing: A Review,” Advanced Information Systems, vol. 8(2), pp. 65–78, 2024, https://doi.org/10.20998/2522-9052.2024.2.08

W. Hilal, S. A. Gadsden, and J. Yawney, “Fraud: A Review of Anomaly Detection Techniques and Recent Advances,” Expert Syst. Appl. 193, 116429, 2022. https://doi.org/10.1016/j.eswa.2021.116429

X. Zhang, F. Guo, T. Chen, L. Pan, G. Beliakov, and J. Wu, “A Brief Survey of Machine Learning and Deep Learning Techniques for E-Commerce Research,” J. Theor. Appl. Electron. Commer. Res. 18, 2188–2216, 2023. https://doi.org/10.3390/jtaer18040110

N. Baisholan, K. Baisholanova, K. Kubayev, Z. Alimzhanova, and N. Baimuldina, “Corporate Network Anomaly Detection Methodology Utilizing Machine Learning Algorithms,” Smart Sci., 12, 666–678, 2024. https://doi.org/10.1080/23080477.2024.2375457

M. Ikermane, M. Mohy-eddine, and Y. Rachidi, “Credit Card Fraud Detection: Comparing Random Forest and XGBoost Models with Explainable AI Interpretations,” In Innovative Technologies on Electrical Power Systems for Smart Cities Infrastructure. ICESST 2024, 126–135. Aboudrar, I., Ilahi Bakhsh, F., Nayyar, A., Ouachtouk, I., Eds.; Sustainable Civil Infrastructures; Springer: Cham, Switzerland, 2025. https://doi.org/10.1007/978-3-031-86705-7_12

I. Achituve, S. Kraus, and J. Goldberger, “Interpretable Online Banking Fraud Detection Based on Hierarchical Attention Mechanism,” In Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Barcelona, Spain, 4–8 May 2020, pp. 1–9.

S. O. Hnatyuk, R. Sh. Berdybayev, V. M. Sydorenko, O. K. Zhigarevych, & T. V. Smirnova, “Event correlation and cybersecurity incident management system at critical infrastructure facilities,” Cybersecurity: Education, Science, Technology, 3(19), 176–196, 2023. https://doi.org/10.28925/2663-4023.2023.19.176196

V. Sydorenko, S. Gnatyuk, A. Tolbatov, A. Fesenko, Y. Yevchenko, & Y. Sotnichenko, “Experimental FMECA-based assessment of the critical information infrastructure importance in aviation,” CEUR Workshop Proceedings, 2732, 2020, 136–156.

A. A. Polozhentsev, & V. M. Sydorenko, “IT threat management method for critical information infrastructure facilities,” Science-Intensive Technologies, 2(62), 143–153, 2024.

K. Suresh Kumar, R. Sudha, T. Suguna, & M. K. Dharani, (n.d.). “An intelligent heartbeat management system utilizing fuzzy logic,” In Advances in Fuzzy-Based Internet of Medical Things (IoMT), 2024, 211–223. https://doi.org/10.1002/9781394242252.ch14

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Published

2026-04-18

How to Cite

Kashkevych , S., & Lastivka , O. (2026). Model for Integrating Different Types of Data in Multilevel Information Structures. Electronics and Control Systems, 2(88), 69–76. https://doi.org/10.18372/1990-5548.88.20968

Issue

Vol. 2 No. 88 (2026)

Section

INFORMATION SYSTEMS AND TECHNOLOGIES

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