Long Short-Term Memory Forecasting for COVID19 Data

Nowadays everyone is talking about Coronavirus 2 or COVID-19. It is a severe acute respiratory syndrome which produces a lot of concerns around the globe. Since data is available for everyone, as well as for the Republic of Serbia, we used it for experiments via a neural network. Here, a long short-term memory approach is applied in order to make experiments with its parameters, such as the number of layers and the number of hidden units. The results show proper modelling from the standard root mean square error standpoint. The paper contribution is related to testing the parameters in the long short-term memory approach for recent data from the Republic of Serbia.