POSSIBILITIES OF USING ARTIFICIAL RADIAL BASIS FUNCTION NEURAL NETWORKS FOR MODELING ECONOMIC PROCESSES

Abstract

The possibility of using artificial radial basis function neural networks for modeling of economic phenomena and processes is shown. The basic characteristics and parameters of an artificial radial basis function neural network are shown and the advantages of using this type of artificial neural networks for modeling economic phenomena and processes are emphasized. Using an artificial radial basis function neural network, together with official statistics for 2010-2017, the modeling of the influence caused by work efficiency indicators of the customs authorities of Ukraine on the indicators of economic security of Ukraine was carried out. The results obtained showed good analytical and prognostic properties of an artificial radial basis function neural network when modeling the impact of customs authorities’ performance on the state’s economic security indicators.