Scientists from Novosibirsk State University have developed a mathematical model using machine learning methods for creating global socio-economic forecasts. This model, designed for the Ministry of Industry and Trade of Russia, predicts key admission figures for higher and secondary educational institutions and analyzes trends over the next 20 years.
In the future, the university plans to expand the use of this system into the business sphere to build forecasts for the development of specific enterprises.
The model takes into account the migration situation in the region, economic and demographic indicators, gross domestic product, investment projects, and other parameters. Based on this data, the model forecasts the number of vacant jobs available at enterprises in various specialties.
The system also compares the forecasted number of graduates with the number of vacancies in the region’s enterprises, helping to achieve equilibrium. The data obtained is used by the Ministry of Education and Science to form and distribute admission quotas for budget places in different regions. The created model also considers major investment projects, allowing the prediction of the required number of graduates in specific specialties to meet the labor market’s needs.
Photo: freepik