Traffic Flow Forecasting Based on Transformer with Diffusion Graph Attention Network
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Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s12239-024-00036-4.pdf
Reference28 articles.
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3. Djenouri, Y., Belhadi, A., Srivastava, G., et al. (2023). Hybrid graph convolution neural network and branch-and-bound optimization for traffic flow forecasting. Future Generation Computer Systems, 139, 100–108.
4. Emami, A., Sarvi, M., & Bagloee, S. A. (2020). Short-term traffic flow prediction based on faded memory Kalman Filter fusing data from connected vehicles and Bluetooth sensors. Simulation Modelling Practice and Theory, 102, 102025.
5. Guo, S., Lin, Y., Li, S., et al. (2019). Deep spatial–temporal 3D convolutional neural networks for traffic data forecasting. IEEE Transactions on Intelligent Transportation Systems, 20(10), 3913–3926.
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