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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 Bayesian Probabilistic Approach for Acoustic Emission‐Based Rail Condition Assessment
Junfang Wang, Xiao Zhou Liu, Yi‐Qing Ni
Computer-Aided Civil and Infrastructure Engineering (2017) Vol. 33, Iss. 1, pp. 21-34
Closed Access | Times Cited: 79

Showing 26-50 of 79 citing articles:

Benchmarking on railway safety performance using Bayesian inference, decision tree and petri-net techniques based on long-term accidental data sets
Panrawee Rungskunroch, Anson Jack, Sakdirat Kaewunruen
Reliability Engineering & System Safety (2021) Vol. 213, pp. 107684-107684
Open Access | Times Cited: 39
Diffuse Ultrasonic Wave-Based Damage Detection of Railway Tracks Using PZT/FBG Hybrid Sensing System
Xiangtao Sun, Chuanrui Guo, Lei Yuan, et al.
Sensors (2022) Vol. 22, Iss. 7, pp. 2504-2504
Open Access | Times Cited: 24
A Survey on Audio-Video Based Defect Detection Through Deep Learning in Railway Maintenance
Lorenzo De Donato, Francesco Flammini, Stefano Marrone, et al.
IEEE Access (2022) Vol. 10, pp. 65376-65400
Open Access | Times Cited: 23
Artificial intelligence in railway infrastructure: current research, challenges, and future opportunities
Wassamon Phusakulkajorn, Alfredo Núñez, Hongrui Wang, et al.
Intelligent Transportation Infrastructure (2023) Vol. 2
Open Access | Times Cited: 15
Damage identification for railway tracks using ultrasound guided wave and hybrid probabilistic deep learning
Yang Zhang, Da-Zhi Dang, You‐Wu Wang, et al.
Construction and Building Materials (2024) Vol. 418, pp. 135466-135466
Closed Access | Times Cited: 4
Acoustic emission source location in complex structures based on artificial potential field-guided rapidly-exploring random tree* and genetic algorithm
Jia-Hao Nie, Dan Li, Hao Wang, et al.
Mechanical Systems and Signal Processing (2024) Vol. 224, pp. 112061-112061
Closed Access | Times Cited: 4
An enhancement method for chloride diffusion coefficient long-term prediction based on Hilbert dynamic probabilistic interpolation and BO-LSTM
Renjie Wu, Yuzhou Wang, Khant Swe Hein, et al.
Measurement (2025), pp. 116820-116820
Closed Access
Predicting rail defect frequency: An integrated approach using fatigue modeling and data analytics
Faeze Ghofrani, Abhishek Pathak, Reza Karami Mohammadi, et al.
Computer-Aided Civil and Infrastructure Engineering (2019) Vol. 35, Iss. 2, pp. 101-115
Closed Access | Times Cited: 35
Study of Building Safety Monitoring by Using Cost-Effective MEMS Accelerometers for Rapid After-Earthquake Assessment with Missing Data
Jian‐Fu Lin, Xueyan Li, Junfang Wang, et al.
Sensors (2021) Vol. 21, Iss. 21, pp. 7327-7327
Open Access | Times Cited: 31
Automatic Detection of Rail Surface Cracks with a Superpixel-Based Data-Driven Framework
Long Wang, Zhuang Li, Zijun Zhang
Journal of Computing in Civil Engineering (2018) Vol. 33, Iss. 1
Closed Access | Times Cited: 35
An adaptive extraction method for rail crack acoustic emission signal under strong wheel-rail rolling noise of high-speed railway
Qiushi Hao, Yi Shen, Yan Wang, et al.
Mechanical Systems and Signal Processing (2020) Vol. 154, pp. 107546-107546
Closed Access | Times Cited: 31
Data-driven approach for post-earthquake condition and reliability assessment with approximate Bayesian computation
Pinghe Ni, Qiang Han, Xiuli Du, et al.
Engineering Structures (2022) Vol. 256, pp. 113940-113940
Closed Access | Times Cited: 17
An efficient approach for guided wave structural monitoring of switch rails via deep convolutional neural network-based transfer learning
Weixu Liu, Zhifeng Tang, Fuzai Lv, et al.
Measurement Science and Technology (2022) Vol. 34, Iss. 2, pp. 024004-024004
Closed Access | Times Cited: 14
Wavelet packet energy-based damage detection using guided ultrasonic waves and support vector machine
Yetao Lyu, Jianwei Yang, Ming Ge, et al.
Measurement Science and Technology (2023) Vol. 34, Iss. 7, pp. 075107-075107
Closed Access | Times Cited: 8
Surface Crack Detection in Precasted Slab Track in High-Speed Rail via Infrared Thermography
Zai-Wei Li, Xiaozhou Liu, Hongyao Lu, et al.
Materials (2020) Vol. 13, Iss. 21, pp. 4837-4837
Open Access | Times Cited: 23
Concise Historic Overview of Rail Corrugation Studies: From Formation Mechanisms to Detection Methods
Qiang Wang, Xinyu Huang, Jun‐Fang Wang, et al.
Buildings (2024) Vol. 14, Iss. 4, pp. 968-968
Open Access | Times Cited: 2
Advancement of data-driven SHM: A research paradigm on AE-based switch rail condition monitoring
Lu Zhou, Si‐Xin Chen, Yi‐Qing Ni, et al.
Journal of Infrastructure Intelligence and Resilience (2024) Vol. 3, Iss. 3, pp. 100107-100107
Open Access | Times Cited: 2
A novel guided wave testing method for identifying rail web cracks using optical fiber Bragg grating sensing and orthogonal matching pursuit
Da-Zhi Dang, You‐Wu Wang, Yi‐Qing Ni
Measurement (2024), pp. 116317-116317
Closed Access | Times Cited: 2
Pareto-Based Maintenance Decisions for Regional Railways With Uncertain Weld Conditions Using the Hilbert Spectrum of Axle Box Acceleration
Alfredo Núñez, Ali Ashraf Jamshidi, Hongrui Wang
IEEE Transactions on Industrial Informatics (2018) Vol. 15, Iss. 3, pp. 1496-1507
Open Access | Times Cited: 22
Probabilistic updating of fishbone model for assessing seismic damage to beam–column connections in steel moment‐resisting frames
Xiaohua Li, Masahiro Kurata
Computer-Aided Civil and Infrastructure Engineering (2018) Vol. 34, Iss. 9, pp. 790-805
Closed Access | Times Cited: 21
A spatially explicit model of postdisaster housing recovery
Ali Nejat, Roxana J. Javid, Souparno Ghosh, et al.
Computer-Aided Civil and Infrastructure Engineering (2019) Vol. 35, Iss. 2, pp. 150-161
Open Access | Times Cited: 18
Bayesian network-based modal frequency–multiple environmental factors pattern recognition for the Xinguang Bridge using long-term monitoring data
He‐Qing Mu, Zhenjie Zheng, Xiaohuan Wu, et al.
Journal of low frequency noise, vibration and active control (2018) Vol. 39, Iss. 3, pp. 545-559
Open Access | Times Cited: 18
On polymorphic uncertainty modeling in shell buckling
Marc Fina, Werner Wagner, Wolfgang Graf
Computer-Aided Civil and Infrastructure Engineering (2023) Vol. 38, Iss. 18, pp. 2632-2647
Open Access | Times Cited: 5
Use of monitored daily extreme stress data for performance prediction of steel bridges: Dynamic linear models and Gaussian mixed particle filter
Xueping Fan, Yuefei Liu
Mechanical Systems and Signal Processing (2018) Vol. 121, pp. 841-855
Closed Access | Times Cited: 15
Condition assessment of high-speed railway track structure based on sparse Bayesian extreme learning machine and Bayesian hypothesis testing
Senrong Wang, Jingze Gao, Chao Lin, et al.
International Journal of Rail Transportation (2022) Vol. 11, Iss. 3, pp. 364-388
Closed Access | Times Cited: 8

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