THE CONCEPT OF INFORMATION-ENTROPY SPACE FOR SYSTEM OBJECTS MODELS BUILDING USED IN SUSTAINABLE DEVELOPMENT TASKS

Abstract

Context. Solving tasks of interdisciplinary research deepening during sustainable development problems solutions search for real social-ecological-economical objects based on systemological modelling and introducing information-entropy space of such objects state and functionality determining for making managerial decisions in uncertainty conditions. Objective. Modelling current situation of researched social-ecological-economical object as the cooperative connection «studied system-environment» based on systemological model, which determines object study goal conditions due to discovery of internal and external factors interaction inside information-entropy space of object functioning representation. Method. The paper presents the logical-experimental research results of complex social-ecological-economical objects state estimation, their development in stochastic environment conditions from the point of view of sustainable development requirements match based on proposed approach. This approach is the systemological basis of studied object entropy model creation and algorithmization by ecological functional of quality of the complex system objects goal state. The quality functional is the interrelation of «object systems-environment» state entropy functions and their interaction processes, which are gotten through monitoring data statistical analyses of objects that belong to technogenic (economical), social and natural systems. Results. The usage of systemology basis complex union for studied object structure identification is suggested for the first time, along with identification of theoretical knowledge for informational entropy for any object system element description and entropic description of states and process. The relative accordance functional is introduced for final evaluation of the studied object equilibrium. It allows to estimate the presence of system and processes unstable points on the basis of nested system structure. It is important for decision making with synergistically positive feedbacks prediction. Conclusions. The systems and process states entropic estimation complex approach is determined. The systemological model «object-environment» is the basis for determining conditions of studied object sustainable development due to usage of found spontaneous and natural synergistically feedbacks. The universal research base for complex systems study was received for their state and functionality estimation due to process synergy and «object-environment» connections that are based on complex usage of systemological modelling and input information entropy estimation.