Author: Sina F. Ardabili; Amir MOSAVI; Pedram Ghamisi; Filip Ferdinand; Annamaria R. Varkonyi-Koczy; Uwe Reuter; Timon Rabczuk; Peter M. Atkinson
Title: COVID-19 Outbreak Prediction with Machine Learning Document date: 2020_4_22
ID: nu0pn2q8_66
Snippet: The copyright holder for this preprint According to Table 18 , the dataset related to scenarios 1 and 2 have different performance values. Accordingly, for Italy, the MLP with 16 neurons provided the highest accuracy for scenario 1 and ANFIS with tri. MF provided the highest accuracy for scenario 2. By considering the average values of the RMSE and correlation coefficient, it can be concluded that scenario 1 is more suitable for modeling outbreak.....
Document: The copyright holder for this preprint According to Table 18 , the dataset related to scenarios 1 and 2 have different performance values. Accordingly, for Italy, the MLP with 16 neurons provided the highest accuracy for scenario 1 and ANFIS with tri. MF provided the highest accuracy for scenario 2. By considering the average values of the RMSE and correlation coefficient, it can be concluded that scenario 1 is more suitable for modeling outbreak cases in Italy, as it provides a higher accuracy (the smallest RMSE and the largest correlation coefficient) than scenario 2.
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