Assessing the Possibility of a Country's Economic Growth Using Dynamic Bayesian Network Models

This paper presents the results of studies on the development of probability-determined models based on Bayesian networks to assess the degree of economic development of Ukraine. Considering that one of the problems in the development of Bayesian networks is the exponential growth in the number of parameters in conditional probability tables (CPT), this study proposes a technique for using noisy-MAX nodes to model economic processes taking into account the time component. It is shown that if the proportion of enterprises that implement innovations is increased now by 31%, while the share of profits of these enterprises increases by only 2%, at the next time step the level of manufacturability and innovation of Ukraine will increase by 81% and will tend to the maximum.