Development of digital economy methods based on hybrid computing intelligence

The paper deals with the problems associated with the development of digital economy methods based on hybrid computing intelligence. We have offered a promising approach of interdisciplinary nature, dealing with such areas as hybrid intellectual systems, synergetic artificial intelligence, neuro and psychophysiology, philosophy, cybernetics, economic and mathematical modeling, etc. The notion of complex, poorly formalized multi-component economic systems (CPFMCESs) functioning in conditions of uncertainty is introduced. At present, the task of developing methods and tools for hybrid economic and mathematical modeling of CPFMCESs and their practical implementation for building hybrid intellectual models (HIMs) of various types of component structures of complex economic systems is extremely important. The concept of a hybrid intellectual model of the CPFMCES with a universal character is offered for the first time, using a set of methods of human intellectual activity (analytical models, expert systems, artificial neural networks, fuzzy systems, genetic algorithms, and simulation statistical models) to solve a problem. A model of the collective creative process (CCP) is typical for a wide class of dynamic problem areas, which has become the methodological basis of hybrid CPFMCES modeling. The CCР model is a formal type of hybrid intelligence, arising through the binding of two entities: the system problem and the proposed method for its solution. The obtained results allowed to formulate a conceptual model of a primary HIM constructor, which provides the basis for a fairly simple and transparent structuring and modeling of CPFMCES, as well as the architecture of a functional hybrid intelligent multi-agent system with self-organization that combines the positive qualities of hybrid decision support systems and multi-agent systems. Using new methods of neurophysiology and neuroimaging of the thinking process in CPFMCES modeling, as well as the approach we have devised for evaluating effective connections between the active regions of the human brain on the basis of experimental data, we have confirmed the effectiveness and versatility of the proposed approach. Currently, the methods and applied tools proposed in the study have been successfully used in the development of hybrid intelligent decision support systems for generating comprehensive enterprise management strategies, in agriculture, engineering, aircraft building, water ecosystems, etc. Research is flourishing in this area.