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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Traffic flow matrix-based graph neural network with attention mechanism for traffic flow prediction
Jian Chen, Zheng Li, Yuzhu Hu, et al.
Information Fusion (2023) Vol. 104, pp. 102146-102146
Closed Access | Times Cited: 54

Showing 1-25 of 54 citing articles:

STGAFormer: Spatial–temporal Gated Attention Transformer based Graph Neural Network for traffic flow forecasting
Zili Geng, Jie Xu, Rongsen Wu, et al.
Information Fusion (2024) Vol. 105, pp. 102228-102228
Closed Access | Times Cited: 25
A systematic review of generative adversarial networks for traffic state prediction: Overview, taxonomy, and future prospects
Ying Li, Fan Bai, Cheng Lyu, et al.
Information Fusion (2025) Vol. 117, pp. 102915-102915
Closed Access | Times Cited: 4
A deep learning approach for electric motor fault diagnosis based on modified InceptionV3
Lifu Xu, Soo Siang Teoh, Haidi Ibrahim
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 9
Spatiotemporal interactive learning dynamic adaptive graph convolutional network for traffic forecasting
Feng Jiang, Xingyu Han, Shiping Wen, et al.
Knowledge-Based Systems (2025), pp. 113115-113115
Closed Access | Times Cited: 1
ST-TDCN: A two-channel tree-structure spatial–temporal convolutional network model for traffic velocity prediction
Zhi-qiang LV, Xiaotong Wang, Zesheng Cheng, et al.
Expert Systems with Applications (2024) Vol. 257, pp. 125053-125053
Closed Access | Times Cited: 4
Context based spatial–temporal graph convolutional networks for traffic prediction
Chaolong Jia, Wenjing Zhang, Yumei He, et al.
Knowledge-Based Systems (2025), pp. 112933-112933
Closed Access
Unifying spatiotemporal and frequential attention for traffic prediction
Qi Guo, Qi Tan, Jun Tang, et al.
Scientific Reports (2025) Vol. 15, Iss. 1
Open Access
Subtractive Clustering-Based Deep Fuzzy System for Time Series Forecasting via Encoding the Long-Term Trend Feature
Yunxia Liu, Songping Meng, Changgeng Zhou, et al.
International Journal of Fuzzy Systems (2025)
Closed Access
DFCNformer: A Transformer Framework for Non-Stationary Time-Series Forecasting Based on De-Stationary Fourier and Coefficient Network
Yuxin Jin, Yuhan Mao, Genlang Chen
Information (2025) Vol. 16, Iss. 1, pp. 62-62
Open Access
Attentional Filtering: Dynamic System State Estimation as an Attention
Andi Lin, Wen-An Zhang, Lei Guo
(2025)
Closed Access
Public data-enhanced multi-stage differentially private graph neural networks
Bingbing Zhang, Heyuan Huang, Lingbo Wei, et al.
Journal of Information Security and Applications (2025) Vol. 89, pp. 103985-103985
Closed Access
A Spatial–Temporal Adaptive Graph Convolutional Network with Multi-Sensor Signals for Tool Wear Prediction
Yu Xia, Guangji Zheng, Ye Li, et al.
Applied Sciences (2025) Vol. 15, Iss. 4, pp. 2058-2058
Open Access
CDTDNet: A Neural Network for Capturing Deep Temporal Dependencies in Time Series
Chuanjiang He, Zhenhong Jia, Jie Hu, et al.
Information Sciences (2025), pp. 121995-121995
Closed Access
Machine Learning-based Accidents Analysis and Risk Early Warning of Hazardous Materials Transportation
Huo Chai, Kewei Dong, Yiming Liang, et al.
Journal of Loss Prevention in the Process Industries (2025), pp. 105594-105594
Closed Access
ASTTN: An Adaptive Spatial–Temporal Transformer Network for traffic flow prediction
Zijie Xue, Linyu Huang, Qian Ning
Engineering Applications of Artificial Intelligence (2025) Vol. 148, pp. 110263-110263
Closed Access
Energy‐Efficient Resource Allocation for Urban Traffic Flow Prediction in Edge‐Cloud Computing
Ahmad Ali, Inam Ullah, Sushil Kumar Singh, et al.
International Journal of Intelligent Systems (2025) Vol. 2025, Iss. 1
Open Access
Real‐Time Monitoring of On‐Board Unit Status in Highway Electronic Toll Collection Systems Using Graphsage‐Based Heterogeneous Graph Learning
Qiang Ren, Changfeng Yan, Fumin Zou, et al.
Concurrency and Computation Practice and Experience (2025) Vol. 37, Iss. 6-8
Closed Access
DPSN-STHA: A Dynamic Perception Model of Similar Nodes with Spatial-Temporal Heterogeneity Attention for Traffic Flow Forecasting
Jinnan Yang, Wentian Cui, Qing Shen, et al.
Information Sciences (2025), pp. 122126-122126
Closed Access
Vehicle Dynamics and Interaction for Trajectory Prediction and Traffic Control
Jian Chen, Shaorui Zhou, Wei Wang, et al.
ACM Transactions on Autonomous and Adaptive Systems (2025)
Closed Access
Urban traffic flow prediction based on multi-spatio-temporal feature fusion
Hui Chen, Jian Huang, Yong Lü, et al.
Neurocomputing (2025), pp. 130117-130117
Open Access
Emerging Trends in Graph Neural Networks for Traffic Flow Prediction: A Survey
Guangrui Fan, Aznul Qalid Md Sabri, Siti Soraya Abdul Rahman, et al.
Archives of Computational Methods in Engineering (2025)
Closed Access
A Meta‐Reinforcement Learning Framework Using Deep Q‐Networks and GCNs for Graph Cluster Representation
Sadia Mughal, Jingsha He, Saqib Hussain, et al.
Software Practice and Experience (2025)
Closed Access
DFF-HGNN: Dual-Feature Fusion Heterogeneous Graph Neural Network
Shaolin Xue, Hua Duan, Yufei Zhao, et al.
Applied Intelligence (2025) Vol. 55, Iss. 7
Closed Access
DyAdapTransformer: dynamic adaptive spatial–temporal graph transformer for traffic flow prediction
Hui Dong, Xiao Pan, Xiao Chen, et al.
Journal of Geographical Systems (2025)
Closed Access
CRRL: Contrastive Region Relevance Learning Framework for cross-city traffic prediction
Genan Dai, Wenfeng Yi, Jinzhou Cao, et al.
Information Fusion (2025), pp. 103215-103215
Closed Access
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