Search academic texts

Information × Registration Number 2121U005350, Article popup.category Стаття Title popup.author popup.publication 01-01-2021 popup.source_user Сумський державний університет popup.source https://essuir.sumdu.edu.ua/handle/123456789/84595 popup.publisher Centre of Sociological Research in co-operation with University of Szczecin (Poland); Széchenyi István University (Hungary); Mykolas Romeris University (Lithuania); Dubcek University of Trencín, Faculty of Social and Economic Relations (Slovak Republic) Description The article uses neural networks to model the effects of quarantine restrictions on the most important indicators of the country's socio-economic development. The authors selected the most relevant indicators and formed a specific sequence of its calculation to study the direction of transforming the trajectory of socio-economic development of a particular country due to quarantine restrictions. They used a multilayer MLP perceptron and networks based on radial basis functions. They chose BFGS and RBFT algorithms in neural network modeling. Collinearity study was the basis for data mining in terms of key factors of change. The author's approach is unique due to an iterative procedure of numerical optimization and quasi-Newton methods ("self-learning" and step-by-step "improvement" of neural networks). The model projected gross domestic product and the number of unemployed in the country affected by the COVID-19 pandemic over the three years. popup.nrat_date 2025-05-12 Close