Research Article
AGCN-T: A Traffic Flow Prediction Model for Spatial-Temporal Network Dynamics
| Time (min) | Evaluation Metrics | PeMSD7 | Seattle | Los-loop | Adj | Cov | PPS | Adj | Cov | PPS | Adj | Cov | PPS |
| 15 | MAE | 5.5110 | 4.5991 | 4.3097 | 6.9075 | 5.6525 | 5.1017 | 5.6016 | 4.6670 | 4.2835 | MAPE (%) | 13.7036 | 11.2313 | 10.4292 | 18.9328 | 15.5131 | 13.8375 | 18.1431 | 14.1301 | 12.5277 | RMSE | 6.0454 | 5.4760 | 4.8063 | 7.2819 | 6.0676 | 5.9637 | 7.0657 | 5.8907 | 4.8178 | 30 | MAE | 5.4933 | 4.6316 | 4.2688 | 6.8810 | 5.5719 | 5.1636 | 5.6003 | 4.6786 | 4.3160 | MAPE (%) | 13.6225 | 11.1215 | 10.3271 | 18.9312 | 15.2345 | 13.8739 | 18.3123 | 13.9333 | 12.1341 | RMSE | 6.0435 | 5.4896 | 4.7950 | 7.2789 | 6.0461 | 5.9858 | 7.0712 | 5.9038 | 4.8330 | 45 | MAE | 5.6563 | 4.5968 | 4.2936 | 6.9114 | 5.7559 | 5.0268 | 5.6209 | 4.7169 | 4.2224 | MAPE (%) | 14.1132 | 10.9292 | 10.4136 | 18.9304 | 15.2732 | 13.5733 | 18.2301 | 13.7352 | 11.9352 | RMSE | 6.0765 | 5.4725 | 4.8009 | 7.2886 | 6.1116 | 5.9479 | 7.0676 | 5.9109 | 4.8066 | 60 | MAE | 5.7055 | 4.6153 | 4.4184 | 6.9624 | 5.8387 | 5.2681 | 5.6838 | 4.7478 | 4.4373 | MAPE (%) | 14.0915 | 11.3228 | 10.8241 | 19.1303 | 15.7121 | 14.1711 | 18.3551 | 14.1812 | 12.4122 | RMSE | 6.0890 | 5.4687 | 4.8245 | 7.2997 | 6.1240 | 6.0076 | 7.0817 | 5.9061 | 4.8595 |
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