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  • Tao Y, Sun P, Boukerche A. A hybrid stacked traffic volume prediction approach for a sparse road network[C]//2019 IEEE Symposium on Computers and Communications (ISCC). 2019: 1-6. IEEE. Link

  • Broucke SV, Piña LM, Do TH, et al. BRUBIKE: A Dataset of Bicycle Traffic and Weather Conditions for Predicting Cycling Flow[C]//2019 IEEE International Smart Cities Conference (ISC2). 2019: 432-437. IEEE. Link Data

  • Liu Z, Huang M, Ye Z, et al. DeepRTP: a deep spatio-temporal residual network for regional traffic prediction[C]//2019 15th International Conference on Mobile Ad-Hoc and Sensor Networks (MSN). 2019: 291-296. IEEE. Link

  • Ali A, Zhu Y, Chen Q, et al. Leveraging spatio-temporal patterns for predicting citywide traffic crowd flows using deep hybrid neural networks[C]//2019 IEEE 25th International Conference on Parallel and Distributed Systems (ICPADS). 2019: 125-132. IEEE. Link

  • Zhang S, Song Y, Jiang D, et al. Noise-identified Kalman filter for short-term traffic flow forecasting[C]//2019 15th International Conference on Mobile Ad-Hoc and Sensor Networks (MSN). 2019: 462-466. IEEE. Link

  • He P, Sun Y, Jiang G, et al. Predicting Travel Time of Bus Journeys with Alternative Bus Services[C]//2019 International Conference on Data Mining Workshops (ICDMW). 2019: 114-123. IEEE. Link

  • Zhou Y, Chen H, Li J, et al. ST-attn: Spatial-temporal attention mechanism for multi-step citywide crowd flow prediction[C]//2019 International Conference on Data Mining Workshops (ICDMW). 2019: 609-614. IEEE. Link

  • Qiu Z, Liu L, Li G, et al. Taxi origin-destination demand prediction with contextualized spatial-temporal network[C]//2019 IEEE International Conference on Multimedia and Expo (ICME). 2019: 760-765. IEEE. Link

  • Yu L, Du B, Hu X, et al. Traffic Accident Prediction Based on Deep Spatio-Temporal Analysis[C]//2019 IEEE SmartWorld, Ubiquitous Intelligence & Computing, Advanced & Trusted Computing, Scalable Computing & Communications, Cloud & Big Data Computing, Internet of People and Smart City Innovation (SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI). 2019: 995-1002. IEEE. Link

  • Wang Y, Guo Y, Wei Z, et al. Traffic flow prediction based on deep neural networks[C]//2019 International Conference on Data Mining Workshops (ICDMW). 2019: 210-215. IEEE. Link

  • Ketabi R, Al-Qathrady M, Alipour B, et al. Vehicular traffic density forecasting through the eyes of traffic cameras; a spatio-temporal machine learning study[C]//Proceedings of the 9th ACM Symposium on Design and Analysis of Intelligent Vehicular Networks and Applications. 2019: 81-88. Link