基于最优汇集时间间隔的城市间断交通流预测
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王殿海,谢瑞,蔡正义
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Prediction of urban interrupted traffic flow based on optimal convergence time interval
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Dian-hai WANG,Rui XIE,Zheng-yi CAI
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表 3 不同预测模型在交叉口1的预测MAPE对比 |
Tab.3 Comparison of MAPE predicted by different prediction models at intersection 1 |
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转向 | 统计学 | | 机器学习 | | 深度学习 | HA | ARIMA | SVR | KNN | CapsNet | GRU | STAWnet | LSTM_BConv | S_L | 26.17 | 32.36 | | 25.63 | 26.17 | | 24.09 | 24.50 | 24.17 | 21.61 | S_S | 15.83 | 26.23 | 13.65 | 14.63 | 18.63 | 13.14 | 14.23 | 12.67 | N_L | 32.72 | 38.89 | 35.06 | 36.10 | 31.72 | 33.14 | 34.10 | 28.45 | N_S | 19.57 | 30.61 | 17.47 | 17.87 | 24.16 | 16.61 | 17.59 | 15.54 | W_L | 29.64 | 43.02 | 36.63 | 38.32 | 43.90 | 32.73 | 34.00 | 29.18 | W_S | 41.02 | 44.29 | 60.60 | 64.07 | 45.96 | 54.29 | 39.59 | 36.88 | E_L | 36.77 | 36.24 | 42.46 | 44.31 | 33.03 | 39.78 | 42.65 | 30.56 | E_S | 31.27 | 33.64 | 30.12 | 31.45 | 26.99 | 28.77 | 30.44 | 25.34 | Mean | 29.12 | 35.66 | 32.70 | 34.12 | 31.06 | 30.37 | 29.60 | 25.03 |
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