A Variational Bayesian Inference-Based En-Decoder Framework for Traffic Flow Prediction-Reference-Cited by-同舟云学术

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A Variational Bayesian Inference-Based En-Decoder Framework for Traffic Flow Prediction

Published:2023 Issue: Volume: Page:1-10
ISSN:1524-9050
Container-title:IEEE Transactions on Intelligent Transportation Systems
language:
Short-container-title:IEEE Trans. Intell. Transport. Syst.

Author:

Kong Jianlei¹^ORCID,Fan Xiaomeng¹^ORCID,Jin Xuebo¹^ORCID,Lin Sen²,Zuo Min³

Affiliation:

1. School of Artificial Intelligence, Beijing Technology and Business University, Beijing, China

2. Research Center of Intelligent Equipment Technology, Beijing Academy of Agriculture and Forestry Sciences, Beijing, China

3. National Engineering Laboratory for Agri-Product Quality Traceability, Beijing Technology and Business University, Beijing, China

Funder

National Natural Science Foundation of China

National Key Research and Development Program of China

Project of Beijing Municipal University Teacher Team Construction Support Plan

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Science Applications,Mechanical Engineering,Automotive Engineering

Link

http://xplorestaging.ieee.org/ielx7/6979/4358928/10132868.pdf?arnumber=10132868

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3. An effective object detector via diffused graphic large selective kernel with one-to-few labelling strategy for small-scaled crop diseases detection;Crop Protection;2024-08

4. Spatial-temporal memory enhanced multi-level attention network for origin-destination demand prediction;Complex & Intelligent Systems;2024-06-14

5. Traffic Anomaly Prediction based on Spatio-Temporal Uncertainty;2024 39th Youth Academic Annual Conference of Chinese Association of Automation (YAC);2024-06-07

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