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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:

A deep reinforcement learning approach for rail renewal and maintenance planning
Reza Karami Mohammadi, Qing He
Reliability Engineering & System Safety (2022) Vol. 225, pp. 108615-108615
Closed Access | Times Cited: 48

Showing 26-50 of 48 citing articles:

Hybrid learning strategies: integrating supervised and reinforcement techniques for railway wheel wear management with limited measurement data
Jessada Sresakoolchai, Chayut Ngamkhanong, Sakdirat Kaewunruen
Frontiers in Built Environment (2025) Vol. 11
Open Access
A Comparative Evaluation of Deep Deterministic Policy Gradient on Aircraft Maintenance Decision Optimization
Yuxuan Sun, Yilin Wang, Jikai Yin, et al.
Lecture notes in electrical engineering (2025), pp. 448-457
Closed Access
Knowledge-enhanced reinforcement learning for multi-machine integrated production and maintenance scheduling
Jueming Hu, Haiyan Wang, Hsiu-Khuern Tang, et al.
Computers & Industrial Engineering (2023) Vol. 185, pp. 109631-109631
Closed Access | Times Cited: 12
A data-driven methodology with a nonparametric reliability method for optimal condition-based maintenance strategies
M. N. Mikhail, Mohamed‐Salah Ouali, Soumaya Yacout
Reliability Engineering & System Safety (2023) Vol. 241, pp. 109668-109668
Closed Access | Times Cited: 11
Maintenance optimization of multi-unit balanced systems using deep reinforcement learning
Hengchang Liu, Bo Li, Fengming Yao, et al.
Reliability Engineering & System Safety (2023) Vol. 244, pp. 109921-109921
Closed Access | Times Cited: 10
Condition-based maintenance with reinforcement learning for refrigeration systems with selected monitored features
Caio Filipe de Lima Munguba, Gustavo de Novaes Pires Leite, Álvaro Antônio Villa Ochoa, et al.
Engineering Applications of Artificial Intelligence (2023) Vol. 122, pp. 106067-106067
Closed Access | Times Cited: 9
Interactive reinforcement learning innovation to reduce carbon emissions in railway infrastructure maintenance
Jessada Sresakoolchai, Sakdirat Kaewunruen
Developments in the Built Environment (2023) Vol. 15, pp. 100193-100193
Open Access | Times Cited: 9
Developing hybrid machine learning models to assign health score to railcar fleets for optimal decision making
Mahyar Ejlali, Ebrahim Arian, Sajjad Taghiyeh, et al.
Expert Systems with Applications (2024) Vol. 250, pp. 123931-123931
Open Access | Times Cited: 3
Leakage diagnosis of natural gas pipeline based on multi-source heterogeneous information fusion
Xingyuan Miao, Hong Zhao
International Journal of Pressure Vessels and Piping (2024) Vol. 209, pp. 105202-105202
Closed Access | Times Cited: 3
Intelligent and adaptive asset management model for railway sections using the iPN method
Ali Saleh, Rasa Remenyte‐Prescott, Darren Prescott, et al.
Reliability Engineering & System Safety (2023) Vol. 241, pp. 109687-109687
Closed Access | Times Cited: 8
A stochastic track maintenance scheduling model based on deep reinforcement learning approaches
Jun Lee, In-Ho Yeo, Younghoon Bae
Reliability Engineering & System Safety (2023) Vol. 241, pp. 109709-109709
Closed Access | Times Cited: 8
Risk-informed operation and maintenance of complex lifeline systems using parallelized multi-agent deep Q-network
Dongkyu Lee, Junho Song
Reliability Engineering & System Safety (2023) Vol. 239, pp. 109512-109512
Open Access | Times Cited: 7
Intelligent construction for the transportation infrastructure: a review
Qing He, Faeze Ghofrani, Tianci Gao, et al.
Intelligent Transportation Infrastructure (2022) Vol. 1
Open Access | Times Cited: 8
Maintenance as a sustainability tool in high-risk process industries: A review and future directions
Djamel Abdelghani Bouabid, Hefaidh Hadef, Fares Innal
Journal of Loss Prevention in the Process Industries (2024) Vol. 89, pp. 105318-105318
Closed Access | Times Cited: 1
A novel sim2real reinforcement learning algorithm for process control
Huiping Liang, Junyao Xie, Biao Huang, et al.
Reliability Engineering & System Safety (2024) Vol. 254, pp. 110639-110639
Closed Access | Times Cited: 1
Multi-Agent Learning of Asset Maintenance Plans through Localised Subnetworks
Marco Pérez Hernández, Alena Puchkova, Ajith Kumar Parlikad
Engineering Applications of Artificial Intelligence (2023) Vol. 127, pp. 107362-107362
Open Access | Times Cited: 3
Investigating the Effect of Grinding Time on High-Speed Grinding of Rails by a Passive Grinding Test Machine
Peng-Zhan Liu, Wenjun Zou, Peng Jin, et al.
Micromachines (2022) Vol. 13, Iss. 12, pp. 2118-2118
Open Access | Times Cited: 3
The Combined Optimization of Railway Track Tamping and Geometry Fine-Tuning Adjustment Allocation with Neuron Network Based Solver
congyang xu, Huakun Sun, Siyuan Zhou, et al.
(2024)
Closed Access
Modeling Expected Failure Considering Repair Time and Degradation: A Rail System Case Study
Maryam Hamidi, Atefe Sedaghat, Amir Gharehgozli, et al.
Journal of Transportation Technologies (2024) Vol. 14, Iss. 02, pp. 236-254
Open Access
An investigation of belief-free DRL and MCTS for inspection and maintenance planning
Daniel Koutas, Elizabeth Bismut, Dániel Straub
Journal of Infrastructure Preservation and Resilience (2024) Vol. 5, Iss. 1
Open Access
Intelligent Petri Nets Based Maintenance Decision-Making Model Considering RCF Degradation
Annemieke Meghoe, Tiedo Tinga, Ali Saleh, et al.
Civil-comp conferences (2024) Vol. 7, pp. 1-12
Open Access
A Deep Reinforcement Learning based Approach for Bridge Health Maintenance
Divija Swetha Gadiraju, Surya Rajalakshmi Muthiah, Deepak Khazanchi
2021 International Conference on Computational Science and Computational Intelligence (CSCI) (2023), pp. 43-48
Closed Access | Times Cited: 1
Optimization of sewer flushing programs: A deep reinforcement learning approach
A. Keshvari Fard, Xian‐Xun Yuan
CRC Press eBooks (2023), pp. 1770-1777
Open Access
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