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intertwin_source_code

FCN : Fully Connected Network

RNN-FCN : Recurrent Neural Network followed by fully connected layer

T-GCN : Temporal graph convolution network for traffic prediction as proposed in -

L. Zhao, Y. Song, C. Zhang, Y. Liu, P. Wang, T. Lin, M. Deng, and H. Li. T-gcn: A temporal graph convolutional network for traffic prediction. IEEE Transactions on Intelligent Transportation Systems, 21(9):3848–3858, 2020

STGCN : Spatio Temporal Graph Convolution Network for traffic predic- tion, as proposed in -

Bing Yu, Haoteng Yin, and Zhanxing Zhu. Spatio-temporal graph convolu- tional networks: A deep learning framework for traffic forecasting. In Pro- ceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, IJCAI-18, pages 3634–3640. International Joint Conferences on Artificial Intelligence Organization, 7 2018

ST-RGAN : Spatio Temporal Residual Graph Attention Network as pro- posed in -

M. Fang, L. Tang, X. Yang, Y. Chen, C. Li, and Q. Li. Ftpg: A fine-grained traffic prediction method with graph attention network using big trace data. IEEE Transactions on Intelligent Transportation Systems, pages 1– 13, 2021

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