Table 17 The evaluation measures of different forecasting models in the recovered cases.
From: A new grey quadratic polynomial model and its application in the COVID-19 in China
GM(1,1) | DGM(1,1) | NGM(1,1,k,c) | GVM(1,1) | PR(2) | GMQP(1,1) | |
|---|---|---|---|---|---|---|
MAEsim | 28.3608 | 18.7810 | 44.8298 | 140.0672 | 39.7383 | 7.6964 |
MAEfit | 66.8066 | 79.9669 | 147.8451 | 816.5043 | 529.8849 | 17.8839 |
MAEall | 35.5694 | 30.2534 | 64.1452 | 266.8992 | 131.6408 | 9.6065 |
MSEsim | 1822.7206 | 770.2744 | 4365.6633 | 39,193.1139 | 2009.7999 | 150.7354 |
MSEfit | 4532.9501 | 12,798.8826 | 22,883.2485 | 696,996.3883 | 340,450.6755 | 474.7209 |
MSEall | 2330.8886 | 3025.6384 | 7837.7105 | 162,531.2278 | 65,467.4640 | 211.4826 |
MAPEsim | 10.4450 | 8.8085 | 15.2606 | 45.7771 | 29.6726 | 4.6767 |
MAPEfit | 3.4499 | 3.2782 | 7.7081 | 39.2977 | 24.0671 | 0.9435 |
MAPEall | 9.1335 | 7.7715 | 13.8446 | 44.5622 | 28.6215 | 3.9767 |
RMSPEsim | 13.5461 | 12.5571 | 18.2762 | 46.4493 | 40.4100 | 7.1431 |
RMSPEfit | 3.6461 | 4.3342 | 8.2016 | 39.2984 | 24.9365 | 1.1304 |
RMSPEEall | 12.3119 | 11.4733 | 16.8524 | 45.1948 | 37.9918 | 6.4573 |
IAsim | 0.9977 | 0.9990 | 0.9946 | 0.9530 | 0.9975 | 0.9998 |
IAfit | 0.9995 | 0.9987 | 0.9973 | 0.8587 | 0.9444 | 0.9999 |
IAall | 0.9990 | 0.9988 | 0.9965 | 0.8986 | 0.9639 | 0.9999 |
Rsim | 0.9993 | 0.9993 | 0.9993 | 0.9992 | 0.9905 | 0.9996 |
Rfit | 0.9991 | 0.9991 | 0.9991 | 0.9999 | 0.9998 | 0.9996 |
Rall | 0.9987 | 0.9985 | 0.9988 | 0.9998 | 0.9832 | 0.9999 |
