Prediction of road traffic flow applying Long Short-Term Memory Model considering impact of COVID-19 in Toyota City
Author:
Affiliation:
1. Toyota Transportation Research Institute, Japan
2. Faculty of science and Technology, TOKYO University of Science, Japan
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3589845.3589855
Reference17 articles.
1. Wei Y. Chen M.C. 2012. Forecasting the short-term metro passenger flow with empirical mode decomposition and neural networks. Transp. Res. Part C: Emerg. S. Hao Transportation Research Part C 107 (2019) 287–300 299 Technol. 21 148–162. Wei Y. Chen M.C. 2012. Forecasting the short-term metro passenger flow with empirical mode decomposition and neural networks. Transp. Res. Part C: Emerg. S. Hao Transportation Research Part C 107 (2019) 287–300 299 Technol. 21 148–162.
2. Deep Neural Networks for traffic flow prediction
3. Short-Term Traffic Flow Prediction Based On Deep Learning Network
4. Long Short-Term Memory
5. Learning to forget: continual prediction with LSTM
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