Graph neural network for traffic forecasting: A survey

Author:

Jiang WeiweiORCID,Luo Jiayun

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Science Applications,General Engineering

Reference259 articles.

1. Traffic flow prediction using graph convolution neural networks;Agafonov,2020

2. Wasserstein gan;Arjovsky,2017

3. Diffusion-convolutional neural networks;Atwood,2016

4. Bai, L., Yao, L., Kanhere, S. S., Wang, X., Liu, W., & Yang, Z. (2019). Spatio-temporal graph convolutional and recurrent networks for citywide passenger demand prediction. In Proceedings of the 28th ACM international conference on information and knowledge management (pp. 2293–2296).

5. Stg2seq: spatial-temporal graph to sequence model for multi-step passenger demand forecasting;Bai,2019

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