Intellectual Evaluation of the Economic Systems’ Performance in Post-Industrial Society

The chapter deals with the difficulty of forecasting economic systems’ work, due to the influence of rapid, largely unpredictable changes in the external environment. Lacking a universal risk management methodology, the search is underway for an individual approach to this issue in each organization. In connection to this, algorithms are used for analysis and risk management, alongside the use of technologies for cognitive modelling of qualitative analysis of economic systems, as well as neuro-fuzzy networks and their quantitative characteristics. Cognitive modelling includes determining target factors, base factors, complex problem situations, and control effects. The cognitive map is drawn, charting the formation of the production programme in the form of an oriented, weighted graph; the vertices of this correspond to the aforementioned factors. Qualitative analysis of this cognitive map is then carried out: arcs between vertices correspond to cause-and-effect relationships between factors and indicate the force of their influence. Processes of perturbation propagation by pathways and cycles are investigated. The hierarchy analysis method is used to verify this. The cognitive map was developed by updating the values of the links without either changing the vertices themselves or adding or removing the links themselves. It is proposed that, to increase the accuracy of forecasting, a neuro-fuzzy network should be created, using the most influential factors of the trained cognitive map for its input. This approach can be used in business intelligence systems for the knowledge economy, based on intelligent decision support systems that use cognitive methods of analysis of expert data, and can also increase efficiency by the parametric configuration of intelligent decision support systems.