A Graph Convolutional Stacked Temporal Attention Neural Network for Traffic Flow Forecasting

Author:

Feng Yushan,Han Fengxia,Zhao Shengjie

Funder

National Key Research and Development Project

National Natural Science Foundation of China

Shanghai Municipal Science and Technology

Natural Science Foundation of Shanghai

Publisher

IEEE

Reference28 articles.

1. Attention is all you need;vaswani;Neural Information Processing Systems,2017

2. A Survey on Modern Deep Neural Network for Traffic Prediction: Trends, Methods and Challenges

3. Analysis of freeway traffic time series data by using box-jenkins techniques;ahmed;Transportation Research Record,1979

4. Application of Subset Autoregressive Integrated Moving Average Model for Short-Term Freeway Traffic Volume Forecasting

5. Short-term prediction of traffic situation using MLP-neural networks;innamaa;Proc 7th World Congr Intell Transp Syst,2000

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1. AdpSTGCN: Adaptive spatial–temporal graph convolutional network for traffic forecasting;Knowledge-Based Systems;2024-10

2. MGSTA : Meta Learning Based Graph Convolutional Stacked Temporal Attention Neural Network for Traffic Flow Forecasting;2024 International Joint Conference on Neural Networks (IJCNN);2024-06-30

3. CRTGAN: Controllable Road Network Graphs Generation via Transformer based GAN;2024 International Joint Conference on Neural Networks (IJCNN);2024-06-30

4. Spatio-Temporal Pre-Training Enhanced Fast Pure Tansformer Network for Traffic Flow Forecasting;2023 International Joint Conference on Neural Networks (IJCNN);2023-06-18

5. Graph Neural Network for Traffic Forecasting: The Research Progress;ISPRS International Journal of Geo-Information;2023-02-27

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