Table 6.
Comparison of prediction performances with existing models.
| Dataset | Indicator | MAE | RMSE | MAPE | TIC | Error Mean | Error STD |
|---|---|---|---|---|---|---|---|
| Beijing | ARIMA | 26.4865 | 36.2374 | 92.8296 | 0.3176 | −0.1317 | 36.3334 |
| RBFNN | 17.0813 | 21.7653 | 62.7264 | 0.1751 | −11.9703 | 18.2263 | |
| SSA-ENN | 14.8237 | 18.7182 | 56.8534 | 0.1593 | −6.4266 | 17.6271 | |
| EEMD-GRNN | 11.3569 | 13.8575 | 41.9101 | 0.1176 | −6.0212 | 12.5142 | |
| EEMD-WOA-BPNN | 6.3748 | 7.7832 | 18.0544 | 0.0647 | −5.2481 | 5.7629 | |
| Pro. Ensemble | 1.6843 | 2.3367 | 5.5600 | 0.0202 | 0.0577 | 2.3422 | |
| Tianjing | ARIMA | 17.4613 | 24.6957 | 35.4034 | 0.2059 | −1.6273 | 24.7075 |
| RBFNN | 12.5062 | 16.2787 | 26.4680 | 0.1376 | −2.2933 | 16.1591 | |
| SSA-ENN | 12.4636 | 16.4413 | 26.2710 | 0.1335 | −5.6593 | 15.4776 | |
| EEMD-GRNN | 7.6808 | 9.7881 | 16.3186 | 0.0815 | −2.8509 | 9.3886 | |
| EEMD-WOA-BPNN | 3.2047 | 3.9304 | 6.6289 | 0.0328 | −0.8012 | 3.8581 | |
| Pro. Ensemble | 1.4745 | 2.0918 | 2.7869 | 0.0176 | 0.0061 | 2.0973 | |
| Baoding | ARIMA | 20.0634 | 26.7218 | 31.9956 | 0.1888 | −3.9880 | 26.4927 |
| RBFNN | 15.0370 | 19.2877 | 25.5808 | 0.1376 | −5.4023 | 18.5648 | |
| SSA-ENN | 13.4114 | 17.4316 | 24.1157 | 0.1275 | −4.2010 | 16.9627 | |
| EEMD-GRNN | 9.5818 | 12.4331 | 17.2851 | 0.0902 | −4.2821 | 11.7035 | |
| EEMD-WOA-BPNN | 5.0988 | 6.7604 | 9.2280 | 0.0495 | −2.2183 | 6.4030 | |
| Pro. Ensemble | 1.4926 | 2.1029 | 2.4427 | 0.0156 | −0.0498 | 2.1079 | |
| Shijiazhuang | ARIMA | 15.5991 | 19.9363 | 25.4303 | 0.1541 | 1.9553 | 19.8929 |
| RBFNN | 13.4980 | 17.7899 | 23.6275 | 0.1310 | −5.9717 | 16.8022 | |
| SSA-ENN | 11.1319 | 15.3624 | 18.5469 | 0.1204 | 0.9266 | 15.3752 | |
| EEMD-GRNN | 15.5582 | 18.5484 | 29.2907 | 0.1326 | −11.1552 | 14.8584 | |
| EEMD-WOA-BPNN | 11.9964 | 15.2740 | 22.6224 | 0.1093 | −9.8333 | 11.7187 | |
| Pro. Ensemble | 1.4004 | 1.8717 | 2.3930 | 0.0143 | −0.0449 | 1.8762 |