多信息融合的时空图卷积交通流量预测模型
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孟闯,王慧
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Traffic flow prediction model based on spatio-temporal graph convolution with multi-information fusion
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Chuang MENG,Hui WANG
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表 3 模型在不同预测时间范围下的RMSE与MAE误差结果 |
Tab.3 RMSE and MAE results of model under different forecasting time ranges |
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$t$ /min | PEMS04 | | PEMS08 | RMSE | MAE | RMSE | MAE | 5 | 28.34 | 18.13 | | 21.54 | 14.13 | 10 | 29.34 | 18.55 | 22.25 | 14.61 | 15 | 30.02 | 19.19 | 23.02 | 15.09 | 20 | 30.86 | 19.72 | 23.78 | 15.76 | 25 | 31.47 | 20.25 | 24.32 | 16.06 | 30 | 32.17 | 20.78 | 24.83 | 16.31 | 35 | 33.07 | 21.31 | 25.46 | 16.83 | 40 | 33.81 | 21.85 | 25.81 | 17.02 | 45 | 34.24 | 22.38 | 26.43 | 17.34 | 50 | 34.72 | 22.91 | 26.91 | 17.56 | 55 | 35.68 | 23.52 | 27.15 | 17.90 | 60 | 36.37 | 23.98 | 27.64 | 18.35 |
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