NEURAL NETWORK MODELING OF THE INTERACTION OF LABOR MARKET SUBJECTS AND EDUCATIONAL SERVICES

The economy of modern Russia is characterized by a number of problems: unemployment and the unemployed population, new requirements on the part of employers for vocational education, the discrepancy between the employers ’personnel needs and the professional capabilities of university graduates. All this is a consequence of the disagreement of the most important areas of modern society - the labor market and education. The increasing complexity of tasks requiring solutions in practice leads to an increase in employers' requirements for the level of training of graduates, which underlies the existing imbalance in the labor market according to qualitative criteria. The article presents the results of neural network modeling of the interaction of subjects of labor markets and educational services. It is shown that to assess the quality of training of specialists according to the criterion of meeting the needs of the regional labor market, indicators of the efficiency of higher education institutions can be used. The rationale for the feasibility of using graduate employment indicators for solving the problems of evaluating and analyzing the effectiveness of higher educational institutions is given. Neural network models of classification, clustering and regression are built for a comprehensive analysis of the relationship between the subjects of the labor market and educational services. Revealed the presence of a strong relationship between the performance indicators of the university and the average salary of graduates in the first year after graduation.

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