Open Access
E3S Web Conf.
Volume 253, 2021
2021 International Conference on Environmental and Engineering Management (EEM 2021)
Article Number 01025
Number of page(s) 4
Section Intelligent Environmental Monitoring and Quality Technology Assessment
Published online 06 May 2021
  1. Vlahogianni, E. I., Karlaftis, M. G., Golias, J. (2014). Short-term traffic forecasting: Where we are and where we’re going. Transportation Research Part C-emerging Technologies,, 3–19. [Google Scholar]
  2. Liu, M. Y., Wu, J. P., Wang, Y. B. (2018). Traffic flow prediction based on deep learning. Journal of System Simulation, 11:4100–4105+4114. [Google Scholar]
  3. Luo, W.H., Dong, B.T., Wang, Z.S. (2017). Short-term traffic flow prediction based on CNN-SVR hybrid deep learning model. Journal of Transportation Systems Engineering and Information Technology, 17(05):68–74. [Google Scholar]
  4. He, Y.X., Yin, F., Yuan, P. (2020). Survey of short-term traffic flow prediction models in intelligent transportation system. Modern Computer. [Google Scholar]
  5. Pascanu, R., Mikolov, T., Bengio, Y. (2013). On the difficulty of training recurrent neural networks. international conference on machine learning. [Google Scholar]
  6. Tian, Y., Pan, L. (2015). Predicting Short-Term Traffic Flow by Long Short-Term Memory Recurrent Neural Network. ieee international conference on smart city socialcom sustaincom. [Google Scholar]
  7. Zeiler, M. D., Fergus, R. (2014). Visualizing and Understanding Convolutional Networks. european conference on computer vision. [Google Scholar]
  8. Salman, A. G., Heryadi, Y., Abdurahman, E.,Suparta, W. (2018). Single Layer & Multi-layer Long Short-Term Memory (LSTM) Model with Intermediate Variables for Weather Forecasting. Procedia Computer Science,, 89–98. [Google Scholar]

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