Vehicular traffic flow prediction using deployed traffic counters in a city

[1]  Junbo Zhang,et al.  Flow Prediction in Spatio-Temporal Networks Based on Multitask Deep Learning , 2020, IEEE Transactions on Knowledge and Data Engineering.

[2]  Naveen Kumar Chikkakrishna,et al.  Short-Term Traffic Prediction Using Sarima and FbPROPHET , 2019, 2019 IEEE 16th India Council International Conference (INDICON).

[3]  Trung Thanh Nguyen,et al.  A Novel Online Dynamic Temporal Context Neural Network Framework for the Prediction of Road Traffic Flow , 2019, IEEE Access.

[4]  Changxi Ma,et al.  Short-Term Traffic Flow Prediction Method for Urban Road Sections Based on Space–Time Analysis and GRU , 2019, IEEE Access.

[5]  Mariano Gallo,et al.  Artificial Neural Networks for Forecasting Passenger Flows on Metro Lines , 2019, Sensors.

[6]  Jing Jiang,et al.  Graph WaveNet for Deep Spatial-Temporal Graph Modeling , 2019, IJCAI.

[7]  Yann Semet,et al.  Expert Competitive Traffic Light Optimization with Evolutionary Algorithms , 2019, VEHITS.

[8]  Germain Forestier,et al.  Deep learning for time series classification: a review , 2018, Data Mining and Knowledge Discovery.

[9]  Xianfeng Tang,et al.  Revisiting Spatial-Temporal Similarity: A Deep Learning Framework for Traffic Prediction , 2018, AAAI.

[10]  Ursula Hübner,et al.  Improving the Prediction of Emergency Department Crowding: A Time Series Analysis Including Road Traffic Flow , 2019, dHealth.

[11]  Bin Ran,et al.  A hybrid deep learning based traffic flow prediction method and its understanding , 2018 .

[12]  Susana Sargento,et al.  PortoLivingLab: An IoT-Based Sensing Platform for Smart Cities , 2018, IEEE Internet of Things Journal.

[13]  Zhanxing Zhu,et al.  Spatio-temporal Graph Convolutional Neural Network: A Deep Learning Framework for Traffic Forecasting , 2017, IJCAI.

[14]  Mauro Conti,et al.  IoT-enabled smart lighting systems for smart cities , 2018, 2018 IEEE 8th Annual Computing and Communication Workshop and Conference (CCWC).

[15]  Yu Zheng,et al.  Deep Spatio-Temporal Residual Networks for Citywide Crowd Flows Prediction , 2016, AAAI.

[16]  Yunpeng Wang,et al.  Long short-term memory neural network for traffic speed prediction using remote microwave sensor data , 2015 .

[17]  Rui Pitarma,et al.  Intelligent management of urban garden irrigation , 2014, 2014 9th Iberian Conference on Information Systems and Technologies (CISTI).

[18]  Nitish Srivastava,et al.  Dropout: a simple way to prevent neural networks from overfitting , 2014, J. Mach. Learn. Res..

[19]  Imrich Chlamtac,et al.  Internet of things: Vision, applications and research challenges , 2012, Ad Hoc Networks.

[20]  Eleni I. Vlahogianni,et al.  Statistical methods versus neural networks in transportation research: Differences, similarities and some insights , 2011 .

[21]  Billy M. Williams,et al.  Modeling and Forecasting Vehicular Traffic Flow as a Seasonal ARIMA Process: Theoretical Basis and Empirical Results , 2003, Journal of Transportation Engineering.

[22]  Jürgen Schmidhuber,et al.  Learning to Forget: Continual Prediction with LSTM , 2000, Neural Computation.

[23]  Edmund S. Yu,et al.  Traffic prediction using neural networks , 1993, Proceedings of GLOBECOM '93. IEEE Global Telecommunications Conference.

[24]  I Okutani,et al.  Dynamic prediction of traffic volume through Kalman Filtering , 1984 .

[25]  A. Savitzky,et al.  Smoothing and Differentiation of Data by Simplified Least Squares Procedures. , 1964 .