TSTA-GCN: trend spatio-temporal traffic flow prediction using adaptive graph convolution network
X
Xinlu Zong
J
Jiawei Guo
(Department of Chemical Engineering)
F
Fucai Liu
(School of Optoelectronic Science and Engineering, University of Electronic Science and Technology of China)
F
Fan Yu
(School of Chemistry and Chemical Engineering/State Key Laboratory Incubation Base for Green Processing of Chemical Engineering)
Article Details
Journal
Scientific Reports
Volume / Issue
Vol. 15, Issue 1
Published
April 18, 2025
ISSN
2045-2322
Publisher
Nature Portfolio
Authors (4)
X
Xinlu Zong
J
Jiawei Guo
Department of Chemical Engineering
F
Fucai Liu
School of Optoelectronic Science and Engineering, University of Electronic Science and Technology of China
F
Fan Yu
School of Chemistry and Chemical Engineering/State Key Laboratory Incubation Base for Green Processing of Chemical Engineering
Related Articles from this Journal
AI models of unstable flow exhibit hallucination
Ramdhan Wibawa, Birendra Jha
Aug 2026
10.1038/s41598-026-64023-8
The MCAA-YOLO + XPBI integrated model provides a hybrid intelligent measurement method for predicting the body weight of Hu sheep
Hang Zhang, Yuang Cheng et al.
Aug 2026
10.1038/s41598-026-64075-w
Application of iron nano-biofertilizers as a sustainable approach to enhance growth and micronutrient uptake in soybean
Ava Mohrazi, Reza Ghasemi-Fasaei
Aug 2026
10.1038/s41598-026-66011-4
Adolescents’ status-dependent public and private conformity to prosocial and antisocial decisions in a public goods game
Niloofar Saeedi, Khatereh Borhani et al.
Aug 2026
10.1038/s41598-026-64831-y
An explainable hierarchical capsule network framework for supporting expert sensory evaluation of herbal medicines with natural language generation
Hyein Lee, Dae-Hyun Jung
Aug 2026
10.1038/s41598-026-64156-w