Chornous G. Modeling of Decision-Making in the Socio-Economic Systems Based on Intellectual Data Analysis.

Conceptual modeling principles of proactive decision-making in socio-economic systems (SES) based on modern information technology shown in the thesis represent a new solution of the scientific problem of decision-making modeling. Analysis of the main trends of modern economic development (globalization, informatization, virtualization, socialization) showed that SES should be considered as a very complex anthropocentric universal type system in the study of decision-making problems. The thesis proposes to present conceptual model of SES through the interaction of subsystems four types (object, project, process, environment) which are combined through dynamic self-organization in a specific configuration for ensure the effective functioning of a complex system. The study showed that the effectiveness of SES in modern conditions largely depends on the system competence of proactivity. That makes it necessary to reorganization of decision-making in SES in order to ensure their successful operation and development on the proactive management basis. The thesis defines the purpose, principles, basic processes, results and methodological basis for proactive management of SES. Analysis of the possibilities and restrictions of widespread methodological approach to modeling and decision support demonstrated the need for the widest involvement of advanced IT, methods and models of intellectual data analysis (IDA) to actual scientific methods arsenal of decision making support in SES. The urgency and complexity of this problem requires a combination of different scientific methods, modeling and instrumental hybridization. The concept of proactive management decision making mechanism modeling developed in the thesis. It involves the representation of socio-economic systems as specific system configurations and the formalization of the basic proactive management processes based on IDA methods and models. The basic elements of concept levels: theoretical and methodological, methodical, instrumental, modeling, practical and organizational and links between levels are determined within the concept. Application level of the concept is implemented as intelligent hybrid information- analytical systems.