Table 5.
Model | MAE | RMSE | MBE | DF | NSE |
---|---|---|---|---|---|
Errors for Training Phase of Models | |||||
SVR | 0.0387 | 0.0389 | 0.0046 | 0.9583 | 0.9195 |
MARS | 0.2700 | 0.3402 | 0.0021 | 0.6560 | 0.4383 |
M5Tree | 0.2541 | 0.3382 | 0.0060 | 0.6782 | 0.4714 |
ANN–BR | 0.2744 | 0.3557 | 0.0035 | 0.6399 | 0.4291 |
ANN–SCG | 0.0847 | 0.1232 | 0.0008 | 0.9066 | 0.8237 |
ANN–BFG | 0.0923 | 0.1253 | 0.0002 | 0.8987 | 0.8079 |
ANN–LM | 0.1246 | 0.1564 | 0.0012 | 0.8620 | 0.7407 |
RBFNN | 0.2185 | 0.2980 | 0.0021 | 0.7346 | 0.5455 |
ANFIS | 0.0165 | 0.0697 | 0.0028 | 0.9829 | 0.9656 |
Errors for Testing Phase of Models | |||||
SVR | 0.2165 | 0.2965 | −0.0041 | 0.7163 | 0.5382 |
MARS | 0.2329 | 0.2870 | −0.1011 | 0.6928 | 0.5032 |
M5Tree | 0.2002 | 0.3055 | −0.1059 | 0.7493 | 0.5730 |
ANN–BR | 0.1774 | 0.2622 | −0.0914 | 0.7779 | 0.6215 |
ANN–SCG | 0.2720 | 0.3842 | −0.0344 | 0.7101 | 0.4198 |
ANN–BFG | 0.2653 | 0.3677 | −0.0489 | 0.7191 | 0.4339 |
ANN–LM | 0.3500 | 0.4289 | −0.1516 | 0.6629 | 0.2533 |
RBFNN | 0.2553 | 0.3395 | −0.0950 | 0.6857 | 0.4554 |
ANFIS | 0.2085 | 0.3292 | 0.0062 | 0.7600 | 0.5551 |