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The article is devoted to the study of the use of neural networks for analysis and forecasting of socio-economic processes, both in Russia and in its individual subjects, on the example of the Khabarovsk territory. The study was carried out by building neural networks to assess, analyze and forecast labor resources in Russia, in the far Eastern Federal district, and as a private aspect – in the Khabarovsk territory. Brief results of scientific analysis and evaluation of modern system of education in preparation of graduates in different clusters of the national economy made the Outlook for reducing the number of labor resources in Khabarovsk territory and the far Eastern Federal district, as threat trends for the effective development of Russia's Eastern territories. The conclusion about efficiency of application of neural networks for estimation of target indicators of the existing regional programmers aimed at education (teaching), employment promotion, support to fill manpower in science-related spheres of economy of the Khabarovsk territory, as well as improving the quality of education of the population to use modern information technologies in the framework of the digital economy, to create jobs in high-tech industries, development of popularization of technical and information-technical education for successful and effective redistribution of jobs for intensive development of the Eastern territories of the Russian Federation.

proceedings of the international conference on economics, management and technologies 2020 (icemt 2020)

Assessment of the Need for Human Resources in the Non-Humanitarian Sphere in the Economy of the Khabarovsk Territory on the Basis of Artificial Neural Networks