Fine-Grained Vessel Traffic Flow Prediction With a Spatio-Temporal Multigraph Convolutional Network-Reference-Cited by-同舟云学术

Fine-Grained Vessel Traffic Flow Prediction With a Spatio-Temporal Multigraph Convolutional Network

Author:

Liang Maohan¹^ORCID,Liu Ryan Wen¹^ORCID,Zhan Yang¹,Li Huanhuan²^ORCID,Zhu Fenghua³^ORCID,Wang Fei-Yue³^ORCID

Affiliation:

1. School of Navigation, Wuhan University of Technology, Wuhan, China

2. School of Engineering, Technology & Maritime Operations, Liverpool John Moores University, Liverpool, U.K.

3. State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, China

Funder

Key-Area Research and Development Program of Guangdong Province

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Science Applications,Mechanical Engineering,Automotive Engineering

Link

Reference63 articles.

1. Spatio-temporal multi-graph convolution network for ride-hailing demand forecasting;geng;Proc AAAI,2019

4. Diffusion convolutional recurrent neural network: Data-driven traffic forecasting;li;Proc ICLR,2018

5. Traffic flow prediction with big data: A deep learning approach;lv;IEEE Trans Intell Transp Syst,2015

Cited by 50 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献