Development of a method for assessing the state of dynamic objects using a population algorithm

Authors

DOI:

https://doi.org/10.15587/1729-4061.2024.308389

Keywords:

complex processes, unimodal functions, multimodal functions, complex and dynamic objects

Abstract

The object of the study is complex dynamic objects with a hierarchical structure. A method for assessing the state of dynamic objects using a population algorithm is proposed. The study is based on the snake optimization algorithm for finding a solution to the state of dynamic objects with a hierarchical structure. For training snake agents (SA), evolving artificial neural networks are used. The originality of the method lies in using additional advanced procedures that allow you:

– to determine the initial position of SA, taking into account the type of uncertainty by using a correction factor for the degree of awareness of the state of the initial situation in relation to the object of analysis;

– to take into account the initial velocity of each SA, which allows studying complex functions;

– to ensure the universality of SA food location search strategies, which allows classifying the type of data to be processed;

– to adjust the SA velocity by adjusting the ambient temperature, which allows priorizing the search for a solution in a certain plane;

– to explore the solution spaces of functions described by non-typical functions, using exploitation mode procedures;

– to flexibly adjust the transition from the SA fighting mode to the mating mode using the food saturation coefficient;

– to replace individuals unsuitable for search using the SA fertility rate;

– to conduct a simultaneous search for a solution in different directions, by changing the ambient temperature and adjusting the food saturation coefficient.

Modeling showed a 13–19 % increase in data processing efficiency by using additional improved procedures.

Author Biographies

Svitlana Kashkevich, National Aviation University

Senior Lecturer

Department of Computerized Management Systems

Ivan Kashkevych, Professional College of Engineering, Management and Land Management of the National Aviation University

Lecturer

Oleksii Kuvshynov, The National University of Defense of Ukraine

Doctor of Technical Sciences, Professor, Deputy head of Center

Centre for Military and Strategic Studies for Scientific Work

Vasyl Kuzavkov, Military Institute of Telecommunications and Information Technologies named after Heroes of Kruty

Doctor of Technical Sciences, Professor, Head of Department

Department of Construction of Telecommunication Systems

Yevhen Zhyvylo, National University “Yuri Kondratyuk Poltava Polytechnic

PhD, Associate Professor

Department of Computer and Information Technologies and Systems

Oksana Dmytriieva, Kharkiv National Automobile and Highway University

Doctor of Economic Sciences, Professor, Head of Department

Department of Economics and Entrepreneurship

Andrii Lebedynskyi, Kharkiv National Automobile and Highway University

PhD, Associate Professor

Department of Computer Systems

Andrii Pysarenko, Scientific-Research Institute of Military Intelligence

Leading Researcher

Yehor Zudikhin, University of Applied Sciences Technikum Wien

Bachelor of Computer Science Student

Faculty Computer Science & Applied Mathematics

Andrii Shyshatskyi, National Aviation University

Doctor of Technical Sciences, Senior Researcher, Associate Professor

Department of Computerized Management Systems

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Development of a method for assessing the state of dynamic objects using a population algorithm

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Published

2024-08-30

How to Cite

Kashkevich, S., Kashkevych, I., Kuvshynov, O., Kuzavkov, V., Zhyvylo, Y., Dmytriieva, O., Lebedynskyi, A., Pysarenko, A., Zudikhin, Y., & Shyshatskyi, A. (2024). Development of a method for assessing the state of dynamic objects using a population algorithm . Eastern-European Journal of Enterprise Technologies, 4(3 (130), 29–36. https://doi.org/10.15587/1729-4061.2024.308389

Issue

Vol. 4 No. 3 (130) (2024): Control processes

Section

Control processes

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Copyright (c) 2024 Svitlana Kashkevich, Ivan Kashkevych, Oleksii Kuvshynov, Vasyl Kuzavkov, Yevhen Zhyvylo, Oksana Dmytriieva, Andrii Lebedynskyi, Andrii Pysarenko, Yehor Zudikhin, Andrii Shyshatskyi

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