PFNet: Large-Scale Traffic Forecasting With Progressive Spatio-Temporal Fusion-Reference-Cited by-同舟云学术

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PFNet: Large-Scale Traffic Forecasting With Progressive Spatio-Temporal Fusion

Published:2023-12 Issue:12 Volume:24 Page:14580-14597
ISSN:1524-9050
Container-title:IEEE Transactions on Intelligent Transportation Systems
language:
Short-container-title:IEEE Trans. Intell. Transport. Syst.

Author:

Wang Chen¹^ORCID,Zuo Kaizhong¹,Zhang Shaokun²^ORCID,Lei Hanwen²,Hu Peng¹,Shen Zhangyi¹,Wang Rui¹,Zhao Peize³

Affiliation:

1. School of Computer and Information, Anhui Normal University, Wuhu, China

2. Department of Computer Science, Key Laboratory on High-Confidence Software Technologies (MOE), School of CS, Peking University, Beijing, China

3. Department of Electronic and Computer Engineering, The Hong Kong University of Science and Technology, Hong Kong, SAR, China

Funder

Natural Science Research Project of Higher Education Institutions in Anhui Province

Research Program of Anhui Higher Education Institutions

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Science Applications,Mechanical Engineering,Automotive Engineering

Link

http://xplorestaging.ieee.org/ielx7/6979/10339106/10195833.pdf?arnumber=10195833

Reference111 articles.

1. Learning Traffic as Images: A Deep Convolutional Neural Network for Large-Scale Transportation Network Speed Prediction

2. A Joint Convolutional Neural Networks and Context Transfer for Street Scenes Labeling

3. Prediction of Road Traffic Congestion Based on Random Forest

4. Spatiotemporal Recurrent Convolutional Networks for Traffic Prediction in Transportation Networks

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

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1. TADGCN: A Time-Aware Dynamic Graph Convolution Network for long-term traffic flow prediction;Expert Systems with Applications;2024-12

2. Camouflaged Object Detection Based on Deep Learning with Attention-Guided Edge Detection and Multi-Scale Context Fusion;Applied Sciences;2024-03-15

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