By using the method of neural network modeling, we have studied the dynamics of innovation activity indicators of the Russian Federation regions. Through the analysis of innovation processes as multifactor phenomena we have determined the dynamics of innovation activity of Russian regions and identified the regions with the highest expenditures on technological innovation. Our research tools were Kohonen self-organizing maps implemented in the Neural Networks module of the Statistica system. As a result of neural network modeling, the regions were divided into five clusters. Composition and characteristics were determined for each cluster. Economic conclusions were made in order to identify the ways of enhancing innovative activity of the Russian Federation regions.
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