IMPLEMENTATION OF UNSUPERVISED LEARNING MODELS FOR ANALYZING THE STATE'S SECURITY LEVEL

Main Article Content

Oleksandr Laktionov
Oleksandr Shefer
Iryna Laktionova
Vasyl Halai
Andrii Podorozhniak

Abstract

Objective. Enhancing the effectiveness of preliminary analysis of the state's security level through the implementation of clustering models. Methodology. The process of creating unsupervised learning models and their peculiarities in tasks of analyzing the state's security level has been investigated. Techniques for creating the basic k-means model and its improvement through the use of Pearson correlation as a distance metric have been considered. Determining cluster centers was performed by both the basic method and the Cochran's maps method. The optimal quality indicator, according to the results of clustering, was considered to be the model demonstrating the minimum value of the Davies-Bouldin index. Results. An improved unsupervised learning model based on the k-means algorithm for analyzing the state's security level has been developed. The model is characterized by two clusters, with centroids determined as 1.112 and 1.009. Scientific novelty. The proposed model for clustering the state's security level differs from existing ones by using as input estimates derived from a comprehensive indicator based on the principles of interaction and emergent properties. This allows obtaining advantages of the clustering model in terms of the Davies-Bouldin index. The existing clustering model demonstrates a value of 0.4765, while the proposed one achieves 0.2166. Practical significance. The proposals serve as a useful additional tool for preliminary analysis of the state's security level during air alerts and extend the functionality of the previously researched forecasting technology.

Article Details

How to Cite
Laktionov, O. ., Shefer , O. ., Laktionova, I. ., Halai , V. ., & Podorozhniak , A. . (2024). IMPLEMENTATION OF UNSUPERVISED LEARNING MODELS FOR ANALYZING THE STATE’S SECURITY LEVEL. Advanced Information Systems, 8(3), 85–91. https://doi.org/10.20998/2522-9052.2024.3.10
Section
Intelligent information systems
Author Biographies

Oleksandr Laktionov, National University “Yuri Kondratyuk Poltava Polytechnic”, Poltava

Candidate of Technical Sciences, Associate Professor of the Department of Automation, Electronics and Telecommunications

Oleksandr Shefer , National University “Yuri Kondratyuk Poltava Polytechnic”, Poltava

Doctor of Technical Sciences, Professor, Head of the Department of Automation, Electronics and Telecommunications

Iryna Laktionova, National University “Yuri Kondratyuk Poltava Polytechnic”, Poltava

Lecturer of the Department of General Linguistics and Foreign Languages

Vasyl Halai , National University “Yuri Kondratyuk Poltava Polytechnic”, Poltava

Candidate of Technical Sciences, Associate Professor of the Department of Automation, Electronics and Telecommunications

Andrii Podorozhniak , National Technical University "Kharkiv Polytechnic Institute", Kharkiv

Candidate of Technical Sciences, Associate Professor, Professor of Computer Engineering and Programming Department

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