UDC 004.65
MULTI-CRITERIA DATA ANALYSIS MODEL FOR DECISION SUPPORT SYSTEM
Y. B. Shcheneva, senior lecturer of CAM department, RSREU, Ryazan, Russia;
orcid.org/0000-0001-6351-0399, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.
A. N. Pylkin, Ph.D. (Engineering), professor of CAM department, RSREU, Ryazan, Russia;
orcid.org/0000-0001-9925-2870, e-mail:This email address is being protected from spambots. You need JavaScript enabled to view it.
E. S. Shchenev, graduate student, RSREU, Ryazan, Russia;
orcid.org/0009-0005-8438-7445, e-mail:This email address is being protected from spambots. You need JavaScript enabled to view it.
The problem of constructing a multi-criteria data analysis model in various applied fields for a decision support system is considered. The aim of the work is to develop a multi-criteria data analysis model on the basis of which flexible and adaptable decision support systems for various fields of knowledge will be im plemented. An innovative approach to optimization model construction based on trajectories analysis in mul tidimensional metric spaces is proposed. The conducted research has shown that the implementation of a multi-criteria decision support system varies significantly. It depends on application area and occurs despite the uniform modeling methodology. Thus, the paper presents a comparative analysis of educational process and technical system modeling results. Particular indicators are selected that reflect information process management dynamics and determine corresponding metric space dimension to formalize the task. The choice of methods for aggregating these indicators into a single generalized criterion in n-dimensional space is substantiated. Based on the results obtained, the principle of constructing trajectories in multidimensional metric spaces is described. This is necessary to increase information process management efficiency in vari ous applications. The research practical significance lies in the possibility of adapting the proposed multi criteria data analysis model for various fields of knowledge. The scientific novelty lies in the automation of decision-making through the usage of modern multi-criteria optimization methods.
Key words: : multi-criteria data analysis, decision support system, multi-criteria optimization, multidi mensional metric spaces, trajectories in metric spaces, information process management, generalized indi cator, applied areas of modeling, decision automation, comparative analysis of models, information system.