Received 25.11.2021, Revised 16.02.2022, Accepted 24.03.2022

Resnet model for the forecasting the expansion of covid-19 in Ukraine

Dmitry Sitnikov, Yuliia Andrusenko

The article considers the ResNet residual neural network model and its application to the problem of predicting the spread of COVID-19 in Ukraine. The study was implemented programmatically in Python. To train the model, time series of morbidity and vaccination rates were used. The result of the model was investigated for accuracy and speed. A comparative analysis of the results showed the performance of the ResNet model relative to another model of convolutional neural networks InceptionTime, but the accuracy of ResNet is lower

predicting, time series, residual neural network, Covid-19, comparative analysis
64-68
Sitnikov, D., & Andrusenko, Y. (2022). Resnet model for the forecasting the expansion of covid-19 in Ukraine. Information Technologies and Computer Engineering, 19(2), 64-68. https://doi.org/10.31649/1999-9941-2022-53-1-64-68

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