MODEL FOR INTEGRATING DIFFERENT TYPES OF DATA IN MULTILEVEL INFORMATION STRUCTURES.
Saved in:
| Title: | MODEL FOR INTEGRATING DIFFERENT TYPES OF DATA IN MULTILEVEL INFORMATION STRUCTURES. |
|---|---|
| Alternate Title: | Модель інтеграції різнотипних даних у багаторівневих інформаційних структурах. |
| Authors: | Kashkevych, Svitlana1 svitlana.kashkevych@npp.kai.edu.ua, Lastivka, Oleksandr1 2450626@stud.kai.edu.ua |
| Source: | Electronics & Control Systems. 2026, Vol. 88 Issue 2, p69-76. 8p. |
| Subjects: | Data integration, Data harmonization, Electronic data processing, Decision support systems, Data structures, Mathematical models, Signal denoising, Metadata |
| 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. [ABSTRACT FROM AUTHOR] |
| Copyright of Electronics & Control Systems is the property of National Aviation University and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
Be the first to leave a comment!
