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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:

Prediction of the crack condition of highway pavements using machine learning models
Sylvester Inkoom, John Sobanjo, Adrian Barbu, et al.
Structure and Infrastructure Engineering (2019) Vol. 15, Iss. 7, pp. 940-953
Closed Access | Times Cited: 64

Showing 1-25 of 64 citing articles:

An engineer's guide to eXplainable Artificial Intelligence and Interpretable Machine Learning: Navigating causality, forced goodness, and the false perception of inference
M.Z. Naser
Automation in Construction (2021) Vol. 129, pp. 103821-103821
Closed Access | Times Cited: 146
Highway 4.0: Digitalization of highways for vulnerable road safety development with intelligent IoT sensors and machine learning
Rajesh Singh, Rohit Sharma, Shaik Vaseem Akram, et al.
Safety Science (2021) Vol. 143, pp. 105407-105407
Closed Access | Times Cited: 113
Predictive models for flexible pavement fatigue cracking based on machine learning
Ali Alnaqbi, Waleed Zeiada, Ghazi G. Al-Khateeb, et al.
Transportation Engineering (2024) Vol. 16, pp. 100243-100243
Open Access | Times Cited: 16
Research and applications of artificial neural network in pavement engineering: A state-of-the-art review
Xu Yang, Jinchao Guan, Ling Ding, et al.
Journal of Traffic and Transportation Engineering (English Edition) (2021) Vol. 8, Iss. 6, pp. 1000-1021
Open Access | Times Cited: 86
An experimental study on the behavior of lime and silica fume treated coir geotextile reinforced expansive soil subgrade
Nitin Tiwari, Neelima Satyam
Engineering Science and Technology an International Journal (2020) Vol. 23, Iss. 5, pp. 1214-1222
Open Access | Times Cited: 80
Intelligent decision-making model in preventive maintenance of asphalt pavement based on PSO-GRU neural network
Jiale Li, Zhishuai Zhang, Xuefei Wang, et al.
Advanced Engineering Informatics (2022) Vol. 51, pp. 101525-101525
Closed Access | Times Cited: 59
Machine learning techniques applied to construction: A hybrid bibliometric analysis of advances and future directions
José García, Gabriel Villavicencio, Francisco Altimiras, et al.
Automation in Construction (2022) Vol. 142, pp. 104532-104532
Closed Access | Times Cited: 42
Automatic pavement damage predictions using various machine learning algorithms: Evaluation and comparison
Ritha Nyirandayisabye, Huixia Li, Qiming Dong, et al.
Results in Engineering (2022) Vol. 16, pp. 100657-100657
Open Access | Times Cited: 42
An Overview of Pavement Degradation Prediction Models
Amir Shtayat, Sara Moridpour, Berthold Best, et al.
Journal of Advanced Transportation (2022) Vol. 2022, pp. 1-15
Open Access | Times Cited: 40
XGBoost-SHAP framework for asphalt pavement condition evaluation
Aakash Gupta, Sachin Gowda, Achyut Tiwari, et al.
Construction and Building Materials (2024) Vol. 426, pp. 136182-136182
Closed Access | Times Cited: 14
CNN-based network with multi-scale context feature and attention mechanism for automatic pavement crack segmentation
Liang Jia, Xingyu Gu, Dong Jiang, et al.
Automation in Construction (2024) Vol. 164, pp. 105482-105482
Closed Access | Times Cited: 8
Comparative Analysis of Machine Learning Models for Prediction of Remaining Service Life of Flexible Pavement
Narjes Nabipour, Nader Karballaeezadeh, Adrienn Dineva, et al.
Mathematics (2019) Vol. 7, Iss. 12, pp. 1198-1198
Open Access | Times Cited: 58
Coupling effect of pond ash and polypropylene fiber on strength and durability of expansive soil subgrades: An integrated experimental and machine learning approach
Nitin Tiwari, Neelima Satyam
Journal of Rock Mechanics and Geotechnical Engineering (2021) Vol. 13, Iss. 5, pp. 1101-1112
Open Access | Times Cited: 54
Intelligent Road Inspection with Advanced Machine Learning; Hybrid Prediction Models for Smart Mobility and Transportation Maintenance Systems
Nader Karballaeezadeh, Farah Zaremotekhases, Shahaboddin Shamshirband, et al.
Energies (2020) Vol. 13, Iss. 7, pp. 1718-1718
Open Access | Times Cited: 52
A review on empirical methods of pavement performance modeling
Aihui Hu, Qiang Bai, Lin Chen, et al.
Construction and Building Materials (2022) Vol. 342, pp. 127968-127968
Closed Access | Times Cited: 33
Prediction model of asphalt pavement functional and structural performance using PSO-BPNN algorithm
Manzhe Xiao, Rong Luo, Yu Chen, et al.
Construction and Building Materials (2023) Vol. 407, pp. 133534-133534
Closed Access | Times Cited: 16
Vision based nighttime pavement cracks pixel level detection by integrating infrared visible fusion and deep learning
Mengnan Shi, H. X. Li, Qiang Yao, et al.
Construction and Building Materials (2024) Vol. 442, pp. 137662-137662
Closed Access | Times Cited: 5
Pavement Crack Rating Using Machine Learning Frameworks: Partitioning, Bootstrap Forest, Boosted Trees, Naïve Bayes, and K -Nearest Neighbors
Sylvester Inkoom, John Sobanjo, Adrian Barbu, et al.
Journal of Transportation Engineering Part B Pavements (2019) Vol. 145, Iss. 3, pp. 04019031-04019031
Closed Access | Times Cited: 45
A hybrid wavelet-optimally-pruned extreme learning machine model for the estimation of international roughness index of rigid pavements
Mosbeh R. Kaloop, Sherif M. El-Badawy, Jungkyu Ahn, et al.
International Journal of Pavement Engineering (2020) Vol. 23, Iss. 3, pp. 862-876
Closed Access | Times Cited: 42
Introducing mathematical modeling to estimate pavement quality index of flexible pavements based on genetic algorithm and artificial neural networks
Shadi Hanandeh
Case Studies in Construction Materials (2022) Vol. 16, pp. e00991-e00991
Open Access | Times Cited: 27
Establishment of probabilistic prediction models for pavement deterioration based on Bayesian neural network
Feng Xiao, Xinyu Chen, Jianchuan Cheng, et al.
International Journal of Pavement Engineering (2022) Vol. 24, Iss. 2
Closed Access | Times Cited: 22
Incorporating cost uncertainty and path dependence into treatment selection for pavement networks
Fengdi Guo, Jeremy Gregory, Randolph Kirchain
Transportation Research Part C Emerging Technologies (2019) Vol. 110, pp. 40-55
Closed Access | Times Cited: 36
Improving asphalt mix design by predicting alligator cracking and longitudinal cracking based on machine learning and dimensionality reduction techniques
Jian Liu, Fangyu Liu, Hongren Gong, et al.
Construction and Building Materials (2022) Vol. 354, pp. 129162-129162
Closed Access | Times Cited: 19
Involving prediction of dynamic modulus in asphalt mix design with machine learning and mechanical-empirical analysis
Jian Liu, Fangyu Liu, Zhen Wang, et al.
Construction and Building Materials (2023) Vol. 407, pp. 133610-133610
Closed Access | Times Cited: 12
Mitigating Traffic Congestion in Smart and Sustainable Cities Using Machine Learning: A Review
Mikkay Wong Ei Leen, Nurul Hanis Aminuddin Jafry, Narishah Mohamed Salleh, et al.
Lecture notes in computer science (2023), pp. 321-331
Closed Access | Times Cited: 9
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