Improving the method for increasing the efficiency of decision-making based on bio-inspired algorithms

Authors

DOI:

https://doi.org/10.15587/1729-4061.2022.268621

Keywords:

uncertainty, monitoring object, data noise, assessment efficiency, reliability of decisions

Abstract

The problem that is solved in the research is to increase the efficiency of assessing the state of the monitoring object while ensuring the given reliability, regardless of the hierarchy of the monitoring object. The object of research is decision support systems. The subject of the research is the process of evaluating the monitoring object using bio-inspired algorithms. The hypothesis of the research is the need to increase the efficiency of the assessment of the state of the monitoring object with the given reliability. In the course of the research, an improved method of increasing the efficiency of decision-making based on bio-inspired algorithms was proposed. General provisions of artificial intelligence theory were used to solve the problem of analyzing the object state in intelligent decision support systems.

The essence of improvement is to use the following procedures:

− taking into account the type of uncertainty about the state of the monitoring object (full uncertainty, partial uncertainty and full awareness);

− taking into account the degree of noise in the data on the state of the monitoring object. Noise refers to the degree of information distortion created by the enemy’s means of electronic and cyber warfare;

− using the ant colony optimization algorithm and the genetic algorithm to find the path metric while assessing the state of the monitoring object;

− deep learning of synthesized ants using evolving artificial neural networks.

An example of using the proposed method in assessing the state of the operational situation of a group of troops (forces) is presented. The specified example showed a 15−22 % increase in the efficiency of data processing using additional improved procedures

Author Biographies

Mykhailo Koval, The National Defence University of Ukraine named after Ivan Cherniakhovskyi

Doctor of Military Sciences, Head

Oleg Sova, Military Institute of Telecommunications and Information Technologies named after Heroes of Kruty

Doctor of Technical Sciences, Senior Researcher, Head of Department

Department of Automated Control Systems

Andrii Shyshatskyi, Research Center for Trophy and Perspective Weapons and Military Equipment

PhD, Senior Researcher, Head of Department

Department of Robotic Systems Research

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

PhD, Head of Department

Research Department of Combat Crews

Nataliia Garashchuk, Scientific-Research Institute of Military Intelligence

Head of Center

Scientific and Methodical Center

Yurii Yivzhenko, State Scientific Institution “Institute of Education Content Modernization”

PhD, Head of Sector

Sector of Scientific and Educational and Methodological Support for the Training of Professional Junior Bachelors in the System of Professional Pre-Higher Education of the Division of Scientific and Methodological Support of Vocational Education

Yuriy Luscshay, National Transport University

PhD, Associate Professor

Department of Transport Law and Logistics

Liudmyla Dovhopoliuk, National Transport University

PhD, Associate Professor

Department of Road Design, Geodesy and Land Management

Oles Haidenko, Kyiv Electromechanical Professional Pre-Higher College

PhD, Lecturer

Mykola Dorofeev, Military Unit A3444

PhD, Leading Researcher, Leading Test Engineer

Scientific and Research Department of Tests of Missile and Artillery Weapons

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Improving the method for increasing the efficiency of decision-making based on bio-inspired algorithms

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Published

2022-12-30

How to Cite

Koval, M., Sova, O., Shyshatskyi, A., Artabaiev, Y., Garashchuk, N., Yivzhenko, Y., Luscshay, Y., Dovhopoliuk, L., Haidenko, O., & Dorofeev, M. (2022). Improving the method for increasing the efficiency of decision-making based on bio-inspired algorithms . Eastern-European Journal of Enterprise Technologies, 6(4 (120), 6–13. https://doi.org/10.15587/1729-4061.2022.268621

Issue

Vol. 6 No. 4 (120) (2022): Mathematics and Cybernetics - applied aspects

Section

Mathematics and Cybernetics - applied aspects

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Copyright (c) 2022 Mykhailo Koval, Oleg Sova, Andrii Shyshatskyi, Yurii Artabaiev, Nataliia Garashchuk, Yurii Yivzhenko, Yuriy Luscshay, Liudmyla Dovhopoliuk, Oles Haidenko, Mykola Dorofeev

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