Table 2.
Average forecasting performance of each model across North and South regions
| Model | Region | MSE | RMSE | MAE |
|
|---|---|---|---|---|---|
| LSTM | North | 0.0309 | 0.1697 | 0.1046 | 0.5056 |
| South | 0.0459 | 0.2073 | 0.1488 | 0.4891 | |
| BiLSTM | North | 0.014 | 0.1157 | 0.0696 | 0.7762 |
| South | 0.0229 | 0.151 | 0.1028 | 0.7454 | |
| CNN-LSTM | North | 0.0376 | 0.1937 | 0.1371 | 0.3969 |
| South | 0.0620 | 0.2487 | 0.1953 | 0.3096 | |
| LSTCNet | North | 0.0106 | 0.099 | 0.0546 | 0.8308 |
| South | 0.0191 | 0.1317 | 0.0695 | 0.7869 | |
| LSTM-Attn. | North | 0.0277 | 0.1656 | 0.1415 | 0.5559 |
| South | 0.0248 | 0.1576 | 0.1321 | 0.6523 | |
| Transformer | North | 0.0187 | 0.1336 | 0.0805 | 0.7016 |
| South | 0.0221 | 0.1446 | 0.1019 | 0.7797 | |
| TCN | North | 0.0375 | 0.1909 | 0.1343 | 0.3990 |
| South | 0.0395 | 0.1944 | 0.1566 | 0.5608 |
Bold values indicate the best performance among all compared models for each region
