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The effectiveness analysis of selected IT tools for predictions of the COVID-19 pandemic

Dymora Paweł, Mazurek Mirosław, Łyczko Kamil

Annals of Computer Science and Information Systems

2022

Vol. 30

583--586

The article presents the problem of the complexity of prediction and the analysis of the effectiveness of selected IT tools in the example of the COVID-19 pandemic data in Poland. The study used a variety of tools and methods to obtain predictions of extinct infections and mortality for each wave of the COVID-19 pandemic. The results are presented for the 4th wave with a detailed description of selected models and methods implemented in the prognostic package of the statistical programming language R, as well as in the Statistica and Microsoft Excel programs. Naive methods, regression models, exponential smoothing methods (including ETS models), ARIMA models, and the method of artificial intelligence - autoregressive models built by neural networks (NNAR) were used. Detailed analysis was performed and the results for each of these methods were compared.