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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:

Train Time Delay Prediction for High-Speed Train Dispatching Based on Spatio-Temporal Graph Convolutional Network
Dalin Zhang, Yunjuan Peng, Yumei Zhang, et al.
IEEE Transactions on Intelligent Transportation Systems (2021) Vol. 23, Iss. 3, pp. 2434-2444
Open Access | Times Cited: 42

Showing 1-25 of 42 citing articles:

Explainable train delay propagation: A graph attention network approach
Ping Huang, Jingwei Guo, Shuming Liu, et al.
Transportation Research Part E Logistics and Transportation Review (2024) Vol. 184, pp. 103457-103457
Closed Access | Times Cited: 10
Enhancing the Understanding of Train Delays With Delay Evolution Pattern Discovery: A Clustering and Bayesian Network Approach
Ping Huang, Thomas Spanninger, Francesco Corman
IEEE Transactions on Intelligent Transportation Systems (2022) Vol. 23, Iss. 9, pp. 15367-15381
Closed Access | Times Cited: 33
Railway network delay evolution: A heterogeneous graph neural network approach
Zhongcan Li, Ping Huang, Chao Wen, et al.
Applied Soft Computing (2024) Vol. 159, pp. 111640-111640
Open Access | Times Cited: 5
An Interpretable Station Delay Prediction Model Based on Graph Community Neural Network and Time-Series Fuzzy Decision Tree
Dalin Zhang, Yi Xu, Yunjuan Peng, et al.
IEEE Transactions on Fuzzy Systems (2022) Vol. 31, Iss. 2, pp. 421-433
Open Access | Times Cited: 23
Deep learning on spatiotemporal graphs: A systematic review, methodological landscape, and research opportunities
Assaad Oussama Zeghina, Aurélie Leborgne, Florence Le Ber, et al.
Neurocomputing (2024) Vol. 594, pp. 127861-127861
Open Access | Times Cited: 4
AP-GRIP evaluation framework for data-driven train delay prediction models: systematic literature review
Kah Yong Tiong, Zhenliang Ma, Carl-William Palmqvist
European Transport Research Review (2025) Vol. 17, Iss. 1
Open Access
A Review of Deep Learning Applications for Railway Safety
Kyue Taek Oh, Mintaek Yoo, Nayoung Jin, et al.
Applied Sciences (2022) Vol. 12, Iss. 20, pp. 10572-10572
Open Access | Times Cited: 20
A high-speed railway network dataset from train operation records and weather data
Dalin Zhang, Yunjuan Peng, Yi Xu, et al.
Scientific Data (2022) Vol. 9, Iss. 1
Open Access | Times Cited: 16
A novel deep learning model for short-term train delay prediction
Bowen Gao, Lei Zhang, Dongxiu Ou, et al.
Information Sciences (2023) Vol. 645, pp. 119270-119270
Closed Access | Times Cited: 9
Cascading Delays for the High-Speed Rail Network Under Different Emergencies: A Double Layer Network Approach
Xingtang Wu, Mingkun Yang, Wenbo Lian, et al.
IEEE/CAA Journal of Automatica Sinica (2022) Vol. 10, Iss. 10, pp. 2014-2025
Closed Access | Times Cited: 12
Analyzing factors contributing to real-time train arrival delays using seemingly unrelated regression models
Kah Yong Tiong, Zhenliang Ma, Carl-William Palmqvist
Transportation Research Part A Policy and Practice (2023) Vol. 174, pp. 103751-103751
Open Access | Times Cited: 7
Towards AI-Driven Transport and Logistics
Amandeep Dhaliwal
Lecture notes in business information processing (2024), pp. 119-131
Closed Access | Times Cited: 2
Bayesian Spatio-Temporal Graph Convolutional Network for Railway Train Delay Prediction
Jianmin Li, Xinyue Xu, Xin Ding, et al.
IEEE Transactions on Intelligent Transportation Systems (2024) Vol. 25, Iss. 7, pp. 8193-8208
Closed Access | Times Cited: 2
Multi-Encoder Spatio-Temporal Feature Fusion Network for Electric Vehicle Charging Load Prediction
Yufan Chen, Mengqin Wang, Yanling Wei, et al.
Journal of Intelligent & Robotic Systems (2024) Vol. 110, Iss. 3
Open Access | Times Cited: 2
Prediction of Train Station Delay Based on Multiattention Graph Convolution Network
Dalin Zhang, Yi Xu, Yunjuan Peng, et al.
Journal of Advanced Transportation (2022) Vol. 2022, pp. 1-12
Open Access | Times Cited: 8
Internet Financial Credit Risk Assessment with Sliding Window and Attention Mechanism LSTM Model
Menggang Li, Zixuan Zhang, Ming Lü, et al.
Tehnicki vjesnik - Technical Gazette (2022) Vol. 30, Iss. 1
Open Access | Times Cited: 8
Delay prediction with spatial–temporal bi-directional LSTM in railway network
Ke Yu, Chuiyun Kong, Limin Zhong, et al.
ICT Express (2023) Vol. 9, Iss. 5, pp. 921-926
Open Access | Times Cited: 4
Prediction of departure delays at original stations using deep learning approaches: A combination of route conflicts and rolling stock connections
Zhongcan Li, Ping Huang, Chao Wen, et al.
Expert Systems with Applications (2023) Vol. 229, pp. 120500-120500
Closed Access | Times Cited: 4
A Data-Driven Surrogate Modeling for Train Rescheduling in High-Speed Railway Networks Under Wind-Caused Speed Restrictions
Ruiguang Liu, Dongliang Cui, Xuewu Dai, et al.
IEEE Transactions on Automation Science and Engineering (2023) Vol. 21, Iss. 2, pp. 1107-1121
Closed Access | Times Cited: 4
Analyzing Factors Contributing to Real-time Train Arrival Delays using Seemingly Unrelated Regression Models
Kah Yong Tiong, Zhenliang Ma, Carl-William Palmqvist
Research Square (Research Square) (2023)
Open Access | Times Cited: 3
Data‐driven train delay prediction incorporating dispatching commands: An XGBoost‐metaheuristic framework
Tianze Gao, Junhua Chen, Huizhang Xu
IET Intelligent Transport Systems (2023) Vol. 18, Iss. 10, pp. 1777-1796
Open Access | Times Cited: 3
Stance Detection Based on User Feature Fusion
Weidong Huang, Yuan Wang, Yang Jin-yuan, et al.
Computational Intelligence and Neuroscience (2022) Vol. 2022, pp. 1-9
Open Access | Times Cited: 5
Modeling Selection for Credit Risk Measurement: Based on Meta Path Features

Tehnicki vjesnik - Technical Gazette (2023) Vol. 30, Iss. 2
Open Access | Times Cited: 2
Multi-step prediction of chlorophyll concentration based on adaptive graph-temporal convolutional network with series decomposition
Ying Chen, Hongbo Zhang, Li Xiao, et al.
Measurement Science and Technology (2023) Vol. 35, Iss. 3, pp. 035801-035801
Open Access | Times Cited: 2
Digital Twin based Train Delay Prediction System: Design and Realization
Shuai Chen, Xingtang Wu, Min Zhou, et al.
2022 41st Chinese Control Conference (CCC) (2022), pp. 305-310
Closed Access | Times Cited: 3
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