PRACTICAL PRINCIPLES OF INTEGRATING ARTIFICIAL INTELLIGENCE INTO THE TECHNOLOGY OF REGIONAL SECURITY PREDICTING

Main Article Content

Oleksandr Shefer
Oleksandr Laktionov
Volodymyr Pents
Alina Hlushko
Nina Kuchuk

Abstract

Objective. The aim is to enhance the efficiency of diagnostics for determining the level of air attack safety through the practical integration principles of artificial intelligence. Methodology. Models and technologies for safety diagnostics of the region (territorial community) have been explored. The process of building an artificial intelligence model requires differentiation of objects at a level to accumulate assessments-characteristics of aerial vehicles. The practical integration principles of artificial intelligence into the forecasting technology are based on the Region Safety Index, used for constructing machine learning models. The optimal machine learning model of the proposed approach is selected from a list of several models. Results. A technology for predicting the level of regional safety based on the Safety Index has been developed. The recommended optimal model is the Random Forest model ([('max_depth', 13), ('max_features', 'sqrt'), ('min_samples_leaf', 1), ('min_samples_split', 2), ('n_estimators', 79)]), demonstrating the most effective quality indicators of MAE; MAX; RMSE 0.005; 0.083; 0.0139, respectively. Scientific Novelty. The proposed approach is based on a linear model of the Region Safety Index, which, unlike existing ones, takes into account the interaction of factors. This allows for advantages of the proposed method over existing approaches in terms of the root mean square error of 0.496; 0.625, respectively. In turn, this influences the quality of machine learning models. Practical Significance. The proposed solutions are valuable for diagnosing the level of safety in the region of Ukraine, particularly in the context of air attacks.

Article Details

How to Cite
Shefer , O. ., Laktionov , O. ., Pents , V. ., Hlushko , A. ., & Kuchuk , N. . (2024). PRACTICAL PRINCIPLES OF INTEGRATING ARTIFICIAL INTELLIGENCE INTO THE TECHNOLOGY OF REGIONAL SECURITY PREDICTING. Advanced Information Systems, 8(1), 86–93. https://doi.org/10.20998/2522-9052.2024.1.11
Section
Intelligent information systems
Author Biographies

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

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

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

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

Volodymyr Pents , National University “Yuri Kondratyuk Poltava Polytechnic”, Poltava

Candidate of Technical Sciences, Associate Professor, Director of the Educational and Research Institute of Information Technologies and Robotics

Alina Hlushko , National University “Yuri Kondratyuk Poltava Polytechnic”, Poltava

Candidate of Economic Sciences, Associate Professor, Associate Professor of the Department of Finance, Banking and Taxation

Nina Kuchuk , National Technical University "Kharkiv Polytechnic Institute", Kharkiv

Doctor of Technical Sciences, Professor, Professor of Computer Engineering and Programming Department

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