Analysis of human capital development in Russia by means of physical culture and sports using neural network modeling

Abstract

Subject. The article investigates the human capital in the regions of the Russian Federation in the context of health promotion and active longevity of the population of the country. Objectives. The purpose is to examine the state of human capital driven by the development of physical culture and sports in Russian regions, using neural network modeling. Methods. Neural networks are used as a method of studying the multidimensional statistical data. The method of data clustering based on neural network modeling is not affiliated with model constraints. This method is aimed at self–training of neural networks, i.e. self-organizing Kohonen maps, and is a promising means of visual representation of multidimensional data space. Results. Using the neural network modeling, we placed 85 Russian regions in six cluster formations. We assessed the influence of each studied indicator on cluster construction. The paper demonstrates a strong difference in the number of regions of the Russian Federation in clusters, presents average values of the considered indicators in clusters for 2021. Conclusions. The study shows uneven development of human capital in Russian regions from the point of view of physical culture and sports, which predetermines different strategies for the development of the regional sports sphere. The positive trend in the number of sports facilities, personnel, and population engaged in physical culture and sports is facilitated by a systems approach based on program documents, which focuses on strengthening the health of citizens and their active longevity.