Table 8.
Results obtained from the soft computing models in the training and testing phase include the different models and seventeen metrics.
| Model | Phase | RMSE | MAE | R | MAPE | VAF | WMAPE | NS | PI | BF | NMBE | WI | MBE | LMI | RSR | a20 | IOA | IOS | Total |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| MD1 | Train | 2 | 1 | 2 | 4 | 2 | 1 | 2 | 2 | 4 | 2 | 1 | 4 | 1 | 2 | 5 | 1 | 2 | 38 |
| Test | 3 | 5 | 4 | 5 | 4 | 5 | 3 | 4 | 3 | 3 | 5 | 6 | 5 | 3 | 5 | 5 | 3 | 71 | |
| Valid | 1 | 1 | 3 | 4 | 1 | 1 | 1 | 3 | 4 | 1 | 5 | 2 | 1 | 1 | 1 | 1 | 1 | 32 | |
| MD10 | Train | 3 | 2 | 3 | 1 | 3 | 2 | 3 | 3 | 3 | 3 | 3 | 2 | 2 | 3 | 1 | 2 | 3 | 42 |
| Test | 2 | 4 | 3 | 4 | 3 | 4 | 2 | 3 | 2 | 2 | 3 | 5 | 4 | 2 | 2 | 4 | 2 | 51 | |
| Valid | 2 | 2 | 3 | 3 | 2 | 2 | 2 | 4 | 5 | 2 | 4 | 1 | 2 | 2 | 1 | 2 | 2 | 41 | |
| MD16 | Train | 5 | 5 | 5 | 3 | 5 | 5 | 5 | 5 | 5 | 5 | 5 | 3 | 5 | 5 | 3 | 5 | 5 | 79 |
| Test | 4 | 1 | 2 | 2 | 2 | 1 | 4 | 2 | 5 | 4 | 1 | 3 | 1 | 4 | 3 | 1 | 4 | 44 | |
| Valid | 3 | 3 | 5 | 2 | 3 | 3 | 3 | 5 | 6 | 3 | 3 | 3 | 3 | 3 | 1 | 3 | 3 | 55 | |
| MD21 | Train | 1 | 3 | 1 | 2 | 1 | 3 | 1 | 1 | 6 | 1 | 2 | 1 | 3 | 1 | 2 | 3 | 1 | 33 |
| Test | 1 | 2 | 1 | 3 | 1 | 2 | 1 | 1 | 4 | 1 | 2 | 4 | 2 | 1 | 3 | 2 | 1 | 32 | |
| Valid | 5 | 5 | 1 | 1 | 5 | 5 | 5 | 2 | 3 | 5 | 1 | 6 | 5 | 5 | 4 | 5 | 5 | 68 | |
| MD26 | Train | 4 | 4 | 4 | 5 | 4 | 4 | 4 | 4 | 2 | 4 | 4 | 5 | 4 | 4 | 4 | 4 | 4 | 68 |
| Test | 5 | 3 | 5 | 1 | 5 | 3 | 5 | 5 | 6 | 5 | 4 | 1 | 3 | 5 | 1 | 3 | 5 | 65 | |
| Valid | 4 | 4 | 2 | 5 | 4 | 4 | 4 | 1 | 2 | 4 | 2 | 5 | 4 | 4 | 5 | 4 | 4 | 62 | |
| MD29 | Train | 6 | 6 | 6 | 6 | 6 | 6 | 6 | 6 | 1 | 6 | 6 | 6 | 6 | 6 | 6 | 6 | 6 | 97 |
| Test | 6 | 6 | 6 | 6 | 6 | 6 | 6 | 6 | 1 | 6 | 6 | 2 | 6 | 6 | 6 | 6 | 6 | 93 | |
| Valid | 6 | 6 | 6 | 6 | 6 | 6 | 6 | 6 | 1 | 6 | 6 | 4 | 6 | 6 | 6 | 6 | 6 | 95 |
Bold shows values correspond to the best model having good prediction results.