Variable-Length Traffic State Prediction and Applications for Urban Network with Adaptive Signal Timing Plan

Author:

Huang haichao,He Hongdi,Zhang Zhe,Ma Qing-hai,Xue Xing-kuo,Zhang Wen-xiu

Publisher

Elsevier BV

Reference39 articles.

1. Exploiting dynamic spatio-temporal graph convolutional neural networks for citywide traffic flows prediction;A Ali;Neural Netw,2022

2. A3T-GCN: Attention Temporal Graph Convolutional Network for Traffic Forecasting;J Bai;ISPRS Int. J. Geo-Inf,2021

3. XGBoost: A Scalable Tree Boosting System;T Chen;Proc. 22nd ACM SIGKDD Int. Conf. Knowl. Discov. Data Min,2016

4. A novel reinforced dynamic graph convolutional network model with data imputation for network-wide traffic flow prediction;Y Chen;Transp. Res. Part C Emerg. Technol,2022

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