A GATs-GAN framework for road traffic states forecasting-Reference-Cited by-同舟云学术

A GATs-GAN framework for road traffic states forecasting

Author:

Xu Dongwei¹^ORCID,Lin Zhenqian¹²^ORCID,Zhou Lei¹²^ORCID,Li Haijian³,Niu Ben⁴

Affiliation:

1. The Department of Institute of Cyberspace Security, Zhejiang University of Technology, Hangzhou, People's Republic of China

2. The Department of College of Information Engineering, Zhejiang University of Technology, Hangzhou, People's Republic of China

3. The Department of Beijing Key Laboratory of Traffic Engineering, Beijing University of Technology, Beijing, People's Republic of China

4. China Academy of Transportation Science (CATS), Beijing, People's Republic of China

Funder

National Natural Science Foundation of China

Zhejiang Provincial Natural Science Foundation

China Postdoctoral Science Foundation

Transportation Engineering of Beijing University of Technology

Publisher

Informa UK Limited

Subject

Transportation,Modeling and Simulation,Software

Link

Reference40 articles.

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4. DyGGAN: Traffic flow prediction based on generative adversarial network and dynamic graph convolution;2023 5th International Conference on Machine Learning, Big Data and Business Intelligence (MLBDBI);2023-12-15