Development of the solution search method using the population algorithm of global search optimization

Authors

DOI:

https://doi.org/10.15587/1729-4061.2023.281007

Keywords:

hybrid actions, artificial neural networks, bio-inspired algorithms, use of forces (troops) of the Naval Forces

Abstract

The research objects are decision making support systems. subject research is a decision making process in management tasks using bio-inspired algorithms. A method of finding solutions using the population algorithm of global search optimization is proposed. Joint use of invasive weed algorithm is proposed, genetic algorithm and evolving artificial neural networks are improved. The method has the following sequence of actions:

‒ an input of initial data;

‒ processing of initial data taking into account the degree of uncertainty;

‒ formation of the optimization vector;

‒ creation of descendant vectors;

‒ ordering of vectors in descending order;

‒ reducing the dimensionality of the feature space;

‒ teaching knowledge bases.

The peculiarity of the proposed method lies in the placement of agents-weeds, taking into account the uncertainty of the initial data, improved procedures for reducing the space of signs about the analysis object state.

Training of synaptic weights of an artificial neural network, type and parameters of the membership function and the architecture of individual elements, and the architecture of an artificial neural network as a whole is carried out. The proposed method was simulated in the MathСad 14 software environment. The task to be solved during the simulation was to determine the route of the ships in the operational zones of the Black and Azov seas in the conditions of hybrid actions of the enemy. The use of the method makes it possible to increase the efficiency of data processing at the level of 21–27 % due to the use of additional improved procedures. The proposed method should be used to solve the problems of evaluating complex and dynamic processes in the interests of solving national security problems

Author Biographies

Stepan Yakymiak, The National Defence University of Ukraine named after Ivan Cherniakhovskyi

PhD, Assosite Professor, Head

Department of Navy

Yevhenii Vdovytskyi, The National Defence University of Ukraine named after Ivan Cherniakhovskyi

Adjunct

The Scientific and Methodological Center of Scientific, Scientific and Technical Activities Organization

Yurii Artabaiev, Research Center for Trophy and Perspective Weapons and Military Equipment

PhD, Head of Department

Research Department of Combat Crews

Larisa Degtyareva, Poltava State Agrarian University

PhD, Associate Professor

Department of Information Systems and Technologies

Yuliia Vakulenko, Poltava State Agrarian University

PhD, Associate Professor

Department of Information Systems and Technologies

Serhii Nevhad, The National Defence University of Ukraine named after Ivan Cherniakhovskyi

PhD, Chief

Language Testing and Research Centre

Vitalii Andronov, Scientific-Research Institute of Military Intelligence

PhD, Head of Department

Roman Lazuta, Military Institute of Telecommunications and Information Technologies named after Heroes of Kruty

Head of Scientific Research Department

The Scientific Center for Communication and Informatization

Petro Shapoval, Central Scientifically-Research Institute of Armaments and Military Equipment of the Armed Forces of Ukraine

PhD

Head

Scientific-Research Laboratory

Yevhen Artamonov, National Aviation University

PhD, Associate Professor

Department of Computerized Control Systems

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Development of the solution search method using the population algorithm of global search optimization

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Published

2023-06-30

How to Cite

Yakymiak, S., Vdovytskyi, Y., Artabaiev, Y., Degtyareva, L., Vakulenko, Y., Nevhad, S., Andronov, V., Lazuta, R., Shapoval, P., & Artamonov, Y. (2023). Development of the solution search method using the population algorithm of global search optimization. Eastern-European Journal of Enterprise Technologies, 3(4 (123), 39–46. https://doi.org/10.15587/1729-4061.2023.281007

Issue

Vol. 3 No. 4 (123) (2023): Mathematics and Cybernetics - applied aspects

Section

Mathematics and Cybernetics - applied aspects

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Copyright (c) 2023 Stepan Yakymiak, Yevhenii Vdovytskyi, Yurii Artabaiev, Larisa Degtyareva, Yuliia Vakulenko, Serhii Nevhad, Vitalii Andronov, Roman Lazuta, Petro Shapoval, Yevhen Artamonov

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