Tetyana Vasilyeva

Department of Finance and Entrepreneurship,

Sumy State University,

Ukraine

tavasilyeva@fem.sumdu.edu.ua

ORCID 0000-0003-0635-7978

Neural network modeling of the economic and social development trajectory transformation due to quarantine restrictions during COVID-19

Olha Kuzmenko

Department of Economic Cybernetics, 

Sumy State University,

Ukraine

o.kuzmenko@uabs.sumdu.edu.ua

ORCID 0000-0001-8520-2266

Mariusz Kuryłowicz

Institute of Security Sciences, Higher School of Criminology and Penitentiary Science in Warsaw, Warsaw, Poland 

mariusz.kurylowicz@wskip.edu.pl 

ORCID 0000-0001-8995-6516

Abstract. 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.

Received: April, 2020

1st Revision: March, 2021

Accepted: June, 2021

DOI: 10.14254/2071-789X.2021/14-2/17

JEL Classification: C45, O18, R13

Keywords: impact of COVID-19, forecast of quarantine measures impact, socio-economic development of Ukraine, economic-mathematical model, neural network