Predicting Human Resource Losses due to the COVID-19 Pandemic in the Context of Personnel Security of Organizations

ABSTRACT

To ensure the economic security of enterprises during the Covid-19 pandemic, it is extremely important to ensure their personnel security, namely to take a set of necessary measures in a timely manner. This is not possible without accurately predicting the staff turnover situation that is directly affected by the pandemic. With this in mind, the paper proposes a mechanism for highly accurate forecasting (error 0.1-0.2%) of staff turnover, taking into account the state of the labor market in the country, which clearly depends on Covid-19. For this purpose, the possibilities of artificial neural networks with radial-basic transmission functions are used. © 2021 IEEE.