An analysis of knowledge representation methods in intelligent decision-making support systems

Oleksandr Gaman, Andrii Shyshatskyi (), Vitalina Babenko, Tetiana Pluhina, Larisa Degtyareva, Olena Shaposhnikova, Sergii Pronin, Nadiia Protas, Tetiana Stasiuk and Inna Kutsenko
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Oleksandr Gaman: Kruty Heroes Military Institute of Telecommunications and Informatization
Andrii Shyshatskyi: National Aviation University
Vitalina Babenko: Kharkiv National Automobile and Highway University
Tetiana Pluhina: Kharkiv National Automobile and Highway University
Larisa Degtyareva: Poltava State Agrarian University
Olena Shaposhnikova: Kharkiv National Automobile and Highway University
Sergii Pronin: Kharkiv National Automobile and Highway University
Nadiia Protas: Poltava State Agrarian University
Tetiana Stasiuk: Military Institute of Telecommunications and Information Technologies named after Heroes of Kruty
Inna Kutsenko: Research Institute of Military Intelligence

Technology audit and production reserves, 2023, vol. 5, issue 2(73), 22-26

Abstract: The scientific task, which is solved in the research, is the analysis of knowledge representation methods in intelligent decision-making support systems. The problem is explained by the fact that the form of knowledge representation significantly affects the characteristics and properties of the system. In order to operate all kinds of knowledge from the real world with the help of a computer, it is necessary to carry out their simulation. In such cases, it is necessary to distinguish knowledge intended for processing by computational devices from knowledge used by humans. In addition, with a large amount of knowledge, it is desirable to simplify the sequential management of individual elements of knowledge. A homogeneous representation leads to a simplification of the logic management mechanism and a simplification of knowledge management. The research is aimed at the analysis of knowledge representation methods in intelligent decision-making support systems. Currently, many models of knowledge representation have been developed. The main models include: logical models; frame model; network models (or semantic networks); production models. Therefore, the object of research is the intelligent decision-making support system. The subject of research is an intelligent decision-making support system.The following is set:– the methods (models, approaches) presented in the research for presenting knowledge in intelligent decision-making support systems in a canonical form are not advisable to use for a number of objective reasons given in subsection 3.1 of the research;– it is necessary to develop new (improvement of existing) representations of knowledge in intelligent decision-making support systems, which will have the advantages of these approaches without their disadvantages.Further improvement of these approaches to reduce the number of shortcomings and limitations of their application should be considered as the direction of further research.

Keywords: decision making support systems; efficiency; cognitive models; global and local optimization (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:baq:taprar:v:5:y:2023:i:2:p:22-26

DOI: 10.15587/2706-5448.2023.289747

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