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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:

Spatiotemporal Attention-Based Graph Convolution Network for Segment-Level Traffic Prediction
Duo Li, Joan Lasenby
IEEE Transactions on Intelligent Transportation Systems (2021) Vol. 23, Iss. 7, pp. 8337-8345
Closed Access | Times Cited: 58

Showing 26-50 of 58 citing articles:

Traffic Flow Prediction Based on Interactive Dynamic Spatio-Temporal Graph Convolution with a Probabilistic Sparse Attention Mechanism
Linlong Chen, Linbiao Chen, Hongyan Wang, et al.
Transportation Research Record Journal of the Transportation Research Board (2024) Vol. 2678, Iss. 9, pp. 837-853
Closed Access | Times Cited: 2
Traffic Flow Prediction Research Based on an Interactive Dynamic Spatial–Temporal Graph Convolutional Probabilistic Sparse Attention Mechanism (IDG-PSAtt)
Zijie Ding, Zhuoshi He, Zhihui Huang, et al.
Atmosphere (2024) Vol. 15, Iss. 4, pp. 413-413
Open Access | Times Cited: 2
A Survey of Traffic Flow Prediction Methods Based on Long Short-Term Memory Networks
Bao‐Lin Ye, Shuang‐Nan Zhang, Lingxi Li, et al.
IEEE Intelligent Transportation Systems Magazine (2024) Vol. 16, Iss. 5, pp. 87-112
Closed Access | Times Cited: 2
Detecting Extreme Traffic Events Via a Context Augmented Graph Autoencoder
Yue Hu, Ao Qu, Daniel B. Work
ACM Transactions on Intelligent Systems and Technology (2022) Vol. 13, Iss. 6, pp. 1-23
Closed Access | Times Cited: 12
Lane-Level Heterogeneous Traffic Flow Prediction: A Spatiotemporal Attention-Based Encoder–Decoder Model
Zheng Yan, Wenquan Li, Wen Zheng, et al.
IEEE Intelligent Transportation Systems Magazine (2022) Vol. 15, Iss. 3, pp. 51-67
Closed Access | Times Cited: 8
Spatial‐temporal correlation graph convolutional networks for traffic forecasting
Ru Huang, Zijian Chen, Guangtao Zhai, et al.
IET Intelligent Transport Systems (2023) Vol. 17, Iss. 7, pp. 1380-1394
Open Access | Times Cited: 4
Optimizing Systemic Redundancy of Traffic Sensor Networks While Maintaining Resilience: New Evidence From Using Graph Learning
Junqing Tang, Shufen Wei, Duo Li, et al.
IEEE Systems Journal (2023) Vol. 17, Iss. 3, pp. 4567-4578
Open Access | Times Cited: 4
Adaptive Spatial-Temporal Graph Convolution Networks for Collaborative Local-Global Learning in Traffic Prediction
Yibi Chen, Yunchuan Qin, Kenli Li, et al.
IEEE Transactions on Vehicular Technology (2023) Vol. 72, Iss. 10, pp. 12653-12663
Closed Access | Times Cited: 4
TCEVis: Visual analytics of traffic congestion influencing factors based on explainable machine learning
Jialu Dong, Huijie Zhang, Meiqi Cui, et al.
Visual Informatics (2023) Vol. 8, Iss. 1, pp. 56-66
Open Access | Times Cited: 4
Cross- and Context-Aware Attention Based Spatial-Temporal Graph Convolutional Networks for Human Mobility Prediction
Zhaobin Mo, Haotian Xiang, Xuan Di
ACM Transactions on Spatial Algorithms and Systems (2024)
Open Access | Times Cited: 1
Urban traffic forecasting using attention based model with GCN and GRU
Ritesh Kumar, Rajesh Panwar, Vijay Kumar Chaurasiya
Multimedia Tools and Applications (2023) Vol. 83, Iss. 16, pp. 47751-47774
Closed Access | Times Cited: 3
Research on Traffic Flow Forecasting Based on Dynamic Spatial-Temporal Transformer
Hong Zhang, Hongyan Wang, Xijun Zhang, et al.
Transportation Research Record Journal of the Transportation Research Board (2023) Vol. 2678, Iss. 7, pp. 301-313
Closed Access | Times Cited: 3
The significance of the convolutional deep learning model in the intelligent collaborative correction of English writing
Hong Wang
3C Tecnología_Glosas de innovación aplicadas a la pyme (2023) Vol. 12, Iss. 01, pp. 142-157
Open Access | Times Cited: 3
Multi-Spatio-Temporal Convolutional Neural Network for Short-Term Metro Passenger Flow Prediction
Ye Lu, Changjiang Zheng, Shukang Zheng, et al.
Electronics (2023) Vol. 13, Iss. 1, pp. 181-181
Open Access | Times Cited: 3
Few-Sample Traffic Prediction With Graph Networks Using Locale as Relational Inductive Biases
Mingxi Li, Yihong Tang, Wei Ma
IEEE Transactions on Intelligent Transportation Systems (2022), pp. 1-15
Open Access | Times Cited: 5
Application of surveying and mapping technology based on deep learning model in petroleum geological exploration
Sheng Sun, Ping Shu
3C Tecnología_Glosas de innovación aplicadas a la pyme (2023) Vol. 12, Iss. 01, pp. 159-174
Open Access | Times Cited: 2
Route planning using divide-and-conquer: A GAT enhanced insertion transformer approach
Pujun Zhang, Shan Liu, Jia Shi, et al.
Transportation Research Part E Logistics and Transportation Review (2023) Vol. 176, pp. 103176-103176
Closed Access | Times Cited: 2
Dynamic Relational Graph Convolutional Network for Metro Passenger Flow Forecasting
Bisheng He, Yongjun Zhu, Andrea D’Ariano, et al.
Operations Research Forum (2023) Vol. 4, Iss. 4
Closed Access | Times Cited: 2
Intersec2vec-TSC: Intersection Representation Learning for Large-Scale Traffic Signal Control
Hao Huang, Zhiqun Hu, Yueting Wang, et al.
IEEE Transactions on Intelligent Transportation Systems (2023) Vol. 25, Iss. 7, pp. 7044-7056
Closed Access | Times Cited: 2
Spatio-Temporal Feature Engineering for Deep Learning Models in Traffic Flow Forecasting
Hongfan Mu, Noura Aljeri, Azzedine Boukerche
IEEE Access (2024) Vol. 12, pp. 76555-76578
Open Access
STC-PSSA: A New Model of Traffic Flow Forecasting Based on Spatiotemporal Convolution and Probabilistic Sparse Self-Attention
Hong Zhang, Linbiao Chen, Xijun Zhang, et al.
Transportation Research Record Journal of the Transportation Research Board (2024)
Closed Access
A multi-scale spatiotemporal network traffic prediction method based on spiking neural model
Erju Li, Bing Li, Hong Peng, et al.
Journal of Membrane Computing (2024)
Closed Access
A Dual-Tower Model for Station-Level Electric Vehicle Charging Demand Prediction
Qinyuan Li, Lei Yao, Shaolin Wang, et al.
Lecture notes in computer science (2024), pp. 481-491
Closed Access
DA-RMN: Denoising Attention Enhanced Recurrent Multi-Graph Convolutional Network for Traffic Flow Prediction
Yinxin Bao, Qin-Qin Shen, Yang Cao, et al.
IEEE Internet of Things Journal (2024) Vol. 12, Iss. 5, pp. 4820-4833
Closed Access
Towards Predictive Pollution Control Through Traffic Flux Forecasting With Deep Learning: A Case Study in the City of Valencia
Miguel G. Folgado, Verónica Sanz, Johannes Hirn, et al.
Applied AI Letters (2024)
Open Access

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