Gaman, O.Shyshatskyi, A.Babenko, V.Pluhina, T.Degtyareva, L. M.Shaposhnikova, O.Pronin, S.Protas, N. M.Stasiuk, T.Kutsenko, I.Дегтярьова, Лариса МиколаївнаПротас, Надія Михайлівна2026-11-122026-11-122023-10-26An 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/10.15587/2706-5448.2023.289747UDC 355/359https://dspace.pdau.edu.ua/handle/123456789/22688The 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.endecision making support systemsefficiencycognitive modelsglobal and local optimizationArticle