ontrol of information flow between the entities of the economic system

Abstract

Models with neural network properties are widely used in the economic and mathematical apparatus for forecasting macroeconomic indicators, as well as in modeling the financial stability of an enterprise, which involves predicting its stability and diagnosing the likelihood of bankruptcy, among other things. The properties of the neural network method also allow for controlling information links between individual entities of the economic system.

The purpose of this article is to explore the possibilities of applying the neural network method to control direct and feedback information links between the entities of a country's economic system.

To achieve this goal, the following research methods were used: the method of systems analysis – to consider the economic system as a holistic structure and to analyze the information links between its entities; literature review on the research topic; the method of generalization – to summarize the research findings.

As a result of the conducted research, it was established that each entity (component of the economic system) not only performs its own function but also controls other entities. A scheme for information exchange between individual entities of the system was proposed. The necessity of adhering to the principle of connecting all entities of the system with both direct and feedback information links was emphasized. It was noted that in the future, it is easier to remove an unnecessary link than to add it later, which could result in the loss of information. It was proven that such a system, where the elements are interconnected by neural network links, can fully function and carry out self-control. Additional components or sub-components can be added to the proposed scheme, or a specific entity can be divided into components, for instance, the market, production, legislative framework, investments, etc.

Future research is seen in detailing the processes of obtaining, processing, and controlling information using the neural network method at the macro level, as well as studying the features of information transmission, the forms of transmitting information from one entity to another using information technologies.