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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:

Generic Dynamic Graph Convolutional Network for traffic flow forecasting
Yi Xu, Liangzhe Han, Tongyu Zhu, et al.
Information Fusion (2023) Vol. 100, pp. 101946-101946
Closed Access | Times Cited: 46

Showing 1-25 of 46 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: 22
COOL: A Conjoint Perspective on Spatio-Temporal Graph Neural Network for Traffic Forecasting
Wei Ju, Yusheng Zhao, Yifang Qin, et al.
Information Fusion (2024) Vol. 107, pp. 102341-102341
Open Access | Times Cited: 15
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: 3
ADCT-Net: Adaptive traffic forecasting neural network via dual-graphic cross-fused transformer
Jianlei Kong, Xiaomeng Fan, Min Zuo, et al.
Information Fusion (2023) Vol. 103, pp. 102122-102122
Closed Access | Times Cited: 26
Time-dependent trip generation for bike sharing planning: A multi-task memory-augmented graph neural network
Yuebing Liang, Zhan Zhao, Fangyi Ding, et al.
Information Fusion (2024) Vol. 106, pp. 102294-102294
Closed Access | Times Cited: 9
STFGCN: Spatial–temporal fusion graph convolutional network for traffic prediction
Hao Li, Jie Liu, Shiyuan Han, et al.
Expert Systems with Applications (2024) Vol. 255, pp. 124648-124648
Closed Access | Times Cited: 6
The survey on multi-source data fusion in cyber-physical-social systems: Foundational infrastructure for industrial metaverses and industries 5.0
Xiao Wang, Yutong Wang, Jing Yang, et al.
Information Fusion (2024) Vol. 107, pp. 102321-102321
Open Access | Times Cited: 5
Traffic Flow Prediction Based on Dynamic Time Slot Graph Convolution
Hongwei Chen, Han Wang, Zexi Chen
Transportation Research Record Journal of the Transportation Research Board (2025)
Closed Access
Lightweighting the prediction process of urban states with parameter sharing and dilated operations
Peixiao Wang, Haolong Yang, Hengcai Zhang, et al.
International Journal of Digital Earth (2025) Vol. 18, Iss. 1
Open Access
Multiple Item Support Constraints Based Frequent Pattern Mining Using Dynamic Prefix Tree
Sudarsan Biswas, Diganta Saha, Rajat Pandit
International Journal of Uncertainty Fuzziness and Knowledge-Based Systems (2025) Vol. 33, Iss. 02, pp. 143-172
Closed Access
Unveiling node relationships for traffic forecasting: A self-supervised approach with MixGT
Qiang Lai, Peng Chen
Information Fusion (2025), pp. 103070-103070
Closed Access
Temporal representation learning enhanced dynamic adversarial graph convolutional network for traffic flow prediction
Linlong Chen, Linbiao Chen, Hongyan Wang, et al.
Scientific Reports (2025) Vol. 15, Iss. 1
Open Access
A unified traffic flow prediction model considering node differences, spatio-temporal features, and local-global dynamics
Qian Shang, Qingyong Zhang, Ju Cao, et al.
Physica A Statistical Mechanics and its Applications (2025), pp. 130554-130554
Closed 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
MixMamba: Time series modeling with adaptive expertise
Alkilane Khaled, Yihang He, Der-Horng Lee
Information Fusion (2024) Vol. 112, pp. 102589-102589
Closed Access | Times Cited: 4
Temporal-aware structure-semantic-coupled graph network for traffic forecasting
Mao Chen, Liangzhe Han, Yi Xu, et al.
Information Fusion (2024) Vol. 107, pp. 102339-102339
Closed Access | Times Cited: 3
MGSFformer: A Multi-Granularity Spatiotemporal Fusion Transformer for Air Quality Prediction
Chengqing Yu, Fei Wang, Yilun Wang, et al.
Information Fusion (2024) Vol. 113, pp. 102607-102607
Closed Access | Times Cited: 3
Multimodal fusion for large-scale traffic prediction with heterogeneous retentive networks
Yimo Yan, Songyi Cui, Jiahui Liu, et al.
Information Fusion (2024), pp. 102695-102695
Closed Access | Times Cited: 3
A hierarchical deep reinforcement learning method for solving urban route planning problems under large-scale customers and real-time traffic conditions
Yuanyuan Li, Qingfeng Guan, Jun Feng Gu, et al.
International Journal of Geographical Information Science (2024), pp. 1-24
Closed Access | Times Cited: 3
An OD time prediction model based on adaptive graph embedding
Rong Wang, Qiang Guo, Shuo Dai, et al.
Physica A Statistical Mechanics and its Applications (2024), pp. 130217-130217
Closed Access | Times Cited: 3
A lightweight spatiotemporal graph dilated convolutional network for urban sensor state prediction
Peixiao Wang, Hengcai Zhang, Shifen Cheng, et al.
Sustainable Cities and Society (2023) Vol. 101, pp. 105105-105105
Closed Access | Times Cited: 7
DMGSTCN: Dynamic Multi-Graph Spatio-Temporal Convolution Network for Traffic Forecasting
Yanjun Qin, Xiaoming Tao, Yuchen Fang, et al.
IEEE Internet of Things Journal (2024) Vol. 11, Iss. 12, pp. 22208-22219
Closed Access | Times Cited: 2
Sparse dynamic graph learning for district heat load forecasting
Yaohui Huang, Yuan Zhao, Zhijin Wang, et al.
Applied Energy (2024) Vol. 371, pp. 123685-123685
Open Access | Times Cited: 2
Hierarchical spatio-temporal graph ODE networks for traffic forecasting
Tao Xu, Jiaming Deng, Ruolin Ma, et al.
Information Fusion (2024) Vol. 113, pp. 102614-102614
Closed Access | Times Cited: 2
Pre-training enhanced spatio-temporal graph neural network for predicting influent water quality and flow rate of wastewater treatment plant: Improvement of forecast accuracy and analysis of related factors
Xuewen Wu, Ming Chen, Tengyi Zhu, et al.
The Science of The Total Environment (2024) Vol. 951, pp. 175411-175411
Closed Access | Times Cited: 2
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