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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:

Near-term train delay prediction in the Dutch railways network
Zhongcan Li, Chao Wen, Rui Hu, et al.
International Journal of Rail Transportation (2020) Vol. 9, Iss. 6, pp. 520-539
Closed Access | Times Cited: 41

Showing 1-25 of 41 citing articles:

A review of train delay prediction approaches
Thomas Spanninger, Alessio Trivella, Beda Büchel, et al.
Journal of Rail Transport Planning & Management (2022) Vol. 22, pp. 100312-100312
Open Access | Times Cited: 41
A review of data-driven approaches to predict train delays
Kah Yong Tiong, Zhenliang Ma, Carl-William Palmqvist
Transportation Research Part C Emerging Technologies (2023) Vol. 148, pp. 104027-104027
Open Access | Times Cited: 34
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
Prediction of the estimated times of arrival of freight train based on operational and geospatial features
Masoud Yaghini, Amirhosein Ezati
Journal of Rail Transport Planning & Management (2025) Vol. 34, pp. 100508-100508
Closed Access
Prediction of train arrival delays considering route conflicts at multi-line stations
Zhongcan Li, Ping Huang, Chao Wen, et al.
Transportation Research Part C Emerging Technologies (2022) Vol. 138, pp. 103606-103606
Open Access | Times Cited: 26
Real-time High-Speed Train Delay Prediction using Seemingly Unrelated Regression Models
Kah Yong Tiong, Zhenliang Ma, Carl-William Palmqvist
Transportation research procedia (2025) Vol. 82, pp. 271-278
Open Access
Data-driven insights to reduce uncertainty from disruptive events in passenger railways
Luís Marques, Sérgio Moro, Pedro Ramos
Public Transport (2025)
Open Access
Predicting primary delay of train services using graph-embedding based machine learning
Ruifan Tang, Ronghui Liu, Zhiyuan Lin
Journal of Rail Transport Planning & Management (2025) Vol. 34, pp. 100518-100518
Open Access
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 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
Prediction of rail transit delays with machine learning: How to exploit open data sources
Malek Sarhani, Stefan Voß
Multimodal Transportation (2024) Vol. 3, Iss. 2, pp. 100120-100120
Open Access | Times Cited: 3
Train delay prediction in Tunisian railway through LightGBM model
Hassiba Laifa, Raoudha Khcherif, Henda Hajjami Ben Ghezalaa
Procedia Computer Science (2021) Vol. 192, pp. 981-990
Open Access | Times Cited: 18
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
A time-series approach for estimated time of arrival prediction in autonomous vehicles
Evangelos Antypas, Georgios Spanos, Antonios Lalas, et al.
Transportation research procedia (2024) Vol. 78, pp. 166-173
Open Access | Times Cited: 2
A novel Markov model for near-term railway delay prediction
Jin Xu, Weiqi Wang, Zheming Gao, et al.
Computers & Industrial Engineering (2023) Vol. 181, pp. 109302-109302
Closed Access | Times Cited: 5
Dynamic train dwell time forecasting: a hybrid approach to address the influence of passenger flow fluctuations
Zishuai Pang, Liwen Wang, Shengjie Wang, et al.
Railway Engineering Science (2023) Vol. 31, Iss. 4, pp. 351-369
Open Access | Times Cited: 5
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
Real-time Train Arrival Time Prediction at Multiple Stations and Arbitrary Times
KahYong Tiong, Zhenliang Ma, Carl-William Palmqvist
2022 IEEE 25th International Conference on Intelligent Transportation Systems (ITSC) (2022), pp. 793-798
Closed Access | Times Cited: 6
Metro train delay-recovery strategy considering passenger waiting time and energy consumption: a real-world case study
Wenxin Li, Qingwei Zhong, Qiyuan Peng, et al.
International Journal of Rail Transportation (2022) Vol. 12, Iss. 1, pp. 76-101
Closed Access | Times Cited: 6
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
Using the gradient boosting decision tree (GBDT) algorithm for a train delay prediction model considering the delay propagation feature
Yuanlai Zhang, Lizi Liao, Qian Yu, et al.
Advances in Production Engineering & Management (2021) Vol. 16, Iss. 3, pp. 285-296
Open Access | Times Cited: 8
Using Delay Logs and Machine Learning to Support Passenger Railway Operations
Willem Klumpenhouwer, Amer Shalaby
Transportation Research Record Journal of the Transportation Research Board (2022) Vol. 2676, Iss. 9, pp. 134-147
Open Access | Times Cited: 4
Online prediction of arrival and departure times in each station for passenger trains using machine learning methods
Shekoofeh Vafaei, Masoud Yaghini
Transportation Engineering (2024) Vol. 16, pp. 100250-100250
Open Access
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