Author: Cosimo Distante; Igor Gadelha Pereira; Luiz Marcos Garcia Goncalves; Prisco Piscitelli; Alessandro Miani
Title: Forecasting Covid-19 Outbreak Progression in Italian Regions: A model based on neural network training from Chinese data Document date: 2020_4_14
ID: azpz6e7q_14
Snippet: We also evaluate the performance of our model by analyzing how close it predicts the next samp in the first phase of the forecasting procedure, that is when real data is available. Figure 4a depicts the daily cases and Figure 4b depicts the cumulative cases of Covid-19 for t Lombardy region. From Figure 4a , we can verify that the model is following the real data on the one-ste ahead forecasting and Figure 4b indicates a plausible trend in the mu.....
Document: We also evaluate the performance of our model by analyzing how close it predicts the next samp in the first phase of the forecasting procedure, that is when real data is available. Figure 4a depicts the daily cases and Figure 4b depicts the cumulative cases of Covid-19 for t Lombardy region. From Figure 4a , we can verify that the model is following the real data on the one-ste ahead forecasting and Figure 4b indicates a plausible trend in the multiple-step-ahead forecasting.
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