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:

Performance of Machine Learning Algorithms in Predicting the Pavement International Roughness Index
MA Bashar, Cristina Torres-Machí
Transportation Research Record Journal of the Transportation Research Board (2021) Vol. 2675, Iss. 5, pp. 226-237
Closed Access | Times Cited: 56

Showing 1-25 of 56 citing articles:

Machine learning techniques for pavement condition evaluation
Nima Sholevar, Amir Golroo, Sahand Roghani Esfahani
Automation in Construction (2022) Vol. 136, pp. 104190-104190
Closed Access | Times Cited: 128

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: 19

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: 17

Prediction of International Roughness Index Based on Stacking Fusion Model
Zhiyuan Luo, Hui Wang, Shenglin Li
Sustainability (2022) Vol. 14, Iss. 12, pp. 6949-6949
Open Access | Times Cited: 68

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

Utilizing machine learning to predict hospital admissions for pediatric COVID-19 patients (PrepCOVID-Machine)
C. Liew, Song‐Quan Ong, David Ng
Scientific Reports (2025) Vol. 15, Iss. 1
Open Access | Times Cited: 1

Pavement roughness index estimation and anomaly detection using smartphones
Qiqin Yu, Yihai Fang, Richard Wix
Automation in Construction (2022) Vol. 141, pp. 104409-104409
Closed Access | Times Cited: 30

Machine Learning for Prediction of the International Roughness Index on Flexible Pavements: A Review, Challenges, and Future Directions
Tiago Tamagusko, Adelino Ferreira
Infrastructures (2023) Vol. 8, Iss. 12, pp. 170-170
Open Access | Times Cited: 16

Artificial intelligence techniques for pavement performance prediction: a systematic review
Jeonghyun Kang, Pejoohan Tavassoti, Muhammad Nuh Ali Reza Chaudhry, et al.
Road Materials and Pavement Design (2024), pp. 1-26
Closed Access | Times Cited: 4

Valuing Imperfect Information from Inspection and Sensing in Condition-Based Roadway Pavement Management with Partially Observable Conditions
Weiwen Zhou, Elise Miller-Hooks, Konstantinos G. Papakonstantinou, et al.
Journal of Transportation Engineering Part B Pavements (2025) Vol. 151, Iss. 2
Closed Access

Prediction of Deflection Bowl Parameters by Gain Ratio Enabled Feature Selection and Machine-Learning Ensembles
Sachin Gowda, Nandan Chikkakalabal Shivaiah, M.A. Jayaram, et al.
Journal of Transportation Engineering Part B Pavements (2025) Vol. 151, Iss. 2
Closed Access

Machine learning techniques for evaluation of permanent deformation responses from geogrid stabilized pavements
Prajwol Tamrakar, Jayhyun Kwon, Mark H. Wayne
Transportation Geotechnics (2025), pp. 101568-101568
Closed Access

Airfield pavement condition prediction with machine learning models for life-cycle cost analysis
April Clemmensen, Hao Wang
International Journal of Pavement Engineering (2024) Vol. 25, Iss. 1
Closed Access | Times Cited: 3

Cost-effective assessment of in-service asphalt pavement condition based on Random Forests and regression analysis
Wangda Guo, Jinxi Zhang, Dandan Cao, et al.
Construction and Building Materials (2022) Vol. 330, pp. 127219-127219
Closed Access | Times Cited: 14

Deep learning for estimating pavement roughness using synthetic aperture radar data
Mohammad Zobair Ibne Bashar, Cristina Torres-Machí
Automation in Construction (2022) Vol. 142, pp. 104504-104504
Closed Access | Times Cited: 14

Development of a Relationship between Pavement Condition Index and International Roughness Index in Rural Road Network
Sasan Adeli, Vahid Najafi Moghaddam Gilani, Mohammad Kashani Novin, et al.
Advances in Civil Engineering (2021) Vol. 2021, Iss. 1
Open Access | Times Cited: 16

Synthesizing the performance of deep learning in vision-based pavement distress detection
Zia U. A. Zihan, Omar Smadi, Miranda Tilberg, et al.
Innovative Infrastructure Solutions (2023) Vol. 8, Iss. 11
Closed Access | Times Cited: 6

Use of data mining techniques to explain the primary factors influencing water sensitivity of asphalt mixtures
Francisco Rebelo, Francisco F. Martins, Hugo Manuel Ribeiro Dias da Silva, et al.
Construction and Building Materials (2022) Vol. 342, pp. 128039-128039
Open Access | Times Cited: 9

Machine Learning Guides the Solution of Blocks Relocation Problem in Container Terminals
Rongye Ye, Rongguang Ye, Sisi Zheng
Transportation Research Record Journal of the Transportation Research Board (2022) Vol. 2677, Iss. 3, pp. 721-737
Closed Access | Times Cited: 9

Multi-time Step Deterioration Prediction of Freeways Using Linear Regression and Machine Learning Approaches: A Case Study
Huu Tran, Dilan Robert, Prageeth Gunarathna, et al.
International Journal of Pavement Research and Technology (2023)
Open Access | Times Cited: 5

An appraisal of statistical and probabilistic models in highway pavements
Jonah Agunwamba, Michael Toryila Tıza, Fidelis Onyebuchi Okafor
Turkish Journal of Engineering (2024) Vol. 8, Iss. 2, pp. 300-329
Open Access | Times Cited: 1

Ensemble Machine Learning Classification Models for Predicting Pavement Condition
Frederick Chung, Andy Doyle, Ernay Robinson, et al.
Transportation Research Record Journal of the Transportation Research Board (2024)
Closed Access | Times Cited: 1

Surrogate modelling of surface roughness for asphalt pavements using artificial neural networks: a mechanistic-empirical approach
Haoran Li, Hessam AzariJafari, Randolph Kirchain, et al.
International Journal of Pavement Engineering (2024) Vol. 25, Iss. 1
Open Access | Times Cited: 1

Physics-guided neural network for predicting international roughness index on flexible pavements considering accuracy, uncertainty and stability
Kun Chen, Mehran Eskandari Torbaghan, Nick Thom, et al.
Engineering Applications of Artificial Intelligence (2024) Vol. 142, pp. 109922-109922
Open Access | Times Cited: 1

Street closure prediction based on the combined conditions of spatially collocated municipal infrastructure assets at the segment level
Tersoo K. Genger, Amin Hammad
Expert Systems with Applications (2023) Vol. 219, pp. 119671-119671
Closed Access | Times Cited: 3

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