Table 3 Result of error evaluation of algorithms for training and validation set.
Error Metrics | Criteria | MLP | RBFNN | CNN | |||
|---|---|---|---|---|---|---|---|
Training | Validation | Training | Validation | Training | Validation | ||
MAE | Lower values indicate higher accuracy | 5.884 | 8.695 | 4.902 | 5.42 | 4.712 | 5.389 |
RMSE | Lower values indicate higher accuracy | 8.381 | 9.08 | 7.523 | 7.908 | 6.510 | 7.488 |
\(\:{\text{R}}^{2}\) | Higher values indicate higher accuracy | 0.9347 | 0.904 | 0.947 | 0.9488 | 0.957 | 0.9544 |
A20 | Higher values indicate higher accuracy | 0.843 | 0.79 | 0.85 | 0.80 | 0.918 | 0.95 |
PI | Lower values indicate higher accuracy | 0.067 | 0.071 | 0.060 | 0.061 | 0.049 | 0.051 |
OF | Lower values indicate higher accuracy | 0.0686 | 0.057 | 0.0498 | |||
