Публікація: An analysis of knowledge representation methods in intelligent decision-making support systems
Ескіз недоступний
Дата
2023-10-26
Автори
Gaman, O.
Shyshatskyi, A.
Babenko, V.
Pluhina, T.
Degtyareva, L. M.
Shaposhnikova, O.
Pronin, S.
Protas, N. M.
Stasiuk, T.
Kutsenko, I.
Назва видання
ISSN
Назва тому
Видання
Technology Audit and Production Reserves
Анотація
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 decisionmaking support system. The subject of research is an intelligent decision-making support system.
Опис
Ключові слова
decision making support systems, efficiency, cognitive models, global and local optimization
Бібліографічний опис
An analysis of knowledge representation methods in intelligent decision-making support systems / O. Gaman et al. Technology Audit and Production Reserves, №5 (2 (73)). Pp. 22–26. DOI: https://doi.org/10.15587/2706-5448.2023.289747