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    Spatiotemporal Traffic Flow Prediction with KNN and LSTM by Xianglong Luo, Danyang Li, Yu Yang, Shengrui Zhang

    Published 2019-01-01
    “…The prediction performance is evaluated with real-time traffic flow data provided by the Transportation Research Data Lab (TDRL) at the University of Minnesota Duluth (UMD) Data Center. Experimental results indicate that the proposed model can achieve a better performance compared with well-known prediction models including autoregressive integrated moving average (ARIMA), support vector regression (SVR), wavelet neural network (WNN), deep belief networks combined with support vector regression (DBN-SVR), and LSTM models, and the proposed model can achieve on average 12.59% accuracy improvement.…”
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