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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:

Predicting uniaxial compressive strength of rocks using ANN models: Incorporating porosity, compressional wave velocity, and schmidt hammer data
Panagiotis G. Asteris, Μαρία Καρόγλου, Athanasia D. Skentou, et al.
Ultrasonics (2024) Vol. 141, pp. 107347-107347
Closed Access | Times Cited: 48

Showing 1-25 of 48 citing articles:

Daily River flow Simulation Using Ensemble Disjoint Aggregating M5-Prime Model
Khabat Khosravi, Nasrin Fathollahzadeh Attar, Sayed M. Bateni, et al.
Heliyon (2024) Vol. 10, Iss. 20, pp. e37965-e37965
Open Access | Times Cited: 14
Stacked-based machine learning to predict the uniaxial compressive strength of concrete materials
Abdelrahman Kamal Hamed, Mohamed Kamel Elshaarawy, Mostafa M. Alsaadawi
Computers & Structures (2025) Vol. 308, pp. 107644-107644
Closed Access | Times Cited: 2
A Novel Hybrid Bayesian-Group-Based Machine Learning (HB-GML) Method for Predicting Uniaxial Compressive Strength (UCS) of Rock
Shenghao Piao, Sheng Huang, Yingjie Wei, et al.
Rock Mechanics and Rock Engineering (2025)
Closed Access | Times Cited: 1
Data-driven predictive model of coal permeability based on microscopic fracture structure characterization
Tianhao Yan, Xiaomeng Xu, Jiafeng Liu, et al.
Journal of Rock Mechanics and Geotechnical Engineering (2025)
Open Access | Times Cited: 1
Utilizing Construction and Demolition Waste in Concrete as a Sustainable Cement Substitute: A Comprehensive Study on Behavior Under Short-term Dynamic and Static Loads via Laboratory and Numerical Analysis
Mohammad Mohtasham Moein, Komeil Rahmati, Ali Mohtasham Moein, et al.
Journal of Building Engineering (2024), pp. 110778-110778
Closed Access | Times Cited: 5
Application of novel deep neural network on prediction of compressive strength of fly ash based concrete
Rahul Biswas, Manish Kumar, Divesh Ranjan Kumar, et al.
Nondestructive Testing And Evaluation (2024), pp. 1-31
Closed Access | Times Cited: 5
BGG-REPT and ROF-REPT: ensemble machine learning models for the prediction of compressive strength of concrete
Binh Thai Pham
Innovative Infrastructure Solutions (2025) Vol. 10, Iss. 2
Closed Access
Optimizing high-strength concrete compressive strength with explainable machine learning
Sanjog Chhetri Sapkota, Christina Panagiotakopoulou, Dipak Dahal, et al.
Multiscale and Multidisciplinary Modeling Experiments and Design (2025) Vol. 8, Iss. 3
Open Access
Evaluation of compression index of red mud by machine learning interpretability methods
Fan Yang, Jieya Zhang, Mingxing Xie, et al.
Computers and Geotechnics (2025) Vol. 181, pp. 107130-107130
Closed Access
Characterizing marble strength and elasticity: Insights from destructive and non-destructive techniques on El Laurel formation (Ecuador)
Wilson F. Espinoza, Randy Moposita, Anthony Torres, et al.
Construction and Building Materials (2025) Vol. 468, pp. 140340-140340
Closed Access
Optimized machine learning models for predicting the tensile strength of high-performance concrete
Divesh Ranjan Kumar, Pramod Kumar, Pradeep Thangavel, et al.
Journal of Structural Integrity and Maintenance (2025) Vol. 10, Iss. 1
Closed Access
Enhancing BOD5 Forecasting Accuracy with the ANN-Enhanced Runge Kutta Model
Rana Muhammad Adnan, Ahmed A. Ewees, Mo Wang, et al.
Journal of environmental chemical engineering (2025), pp. 115430-115430
Closed Access
Fine-tuning of Experimentally Obtained Particle Damper Parameters Using Hybrid Radial Basis Function Neural Network for Vibration Mitigation of a PCB Enclosure
Sunil Kumar, Anil Kumar
Journal of Vibration Engineering & Technologies (2025) Vol. 13, Iss. 2
Closed Access
Machine Learning for predicting strength properties of waste iron slag concrete
Matiur Rahman Raju, Syed Ishtiaq Ahmad, Md Mehedi Hasan, et al.
Heliyon (2025) Vol. 11, Iss. 3, pp. e42133-e42133
Open Access
Improved Boreability Index for Gripper TBMs in Medium- to Strong-Quality Rocks Based on Theoretical Analysis and Field Penetration Tests
Wen‐Kun Yang, Zuyu Chen, Shuangjing Wang, et al.
Rock Mechanics and Rock Engineering (2025)
Closed Access
Comparative use of different AI methods for the prediction of concrete compressive strength
Mouhamadou Amar
Cleaner Materials (2025) Vol. 15, pp. 100299-100299
Open Access
An AutoGluon-enabled robust machine learning model for concrete tensile and compressive strength forecast
Chukwuemeka Daniel, Edith Komo Neufville
International Journal of Construction Management (2025), pp. 1-12
Closed Access
Integrating Multiple Linear Regression Analysis and Machine Learning Models to Predict the Bearing Capacity of Strip Footings on Sandy Clay Slopes
Lindung Zalbuin Mase, Rena Misliniyati, Nia Afriantialina Muharama, et al.
Transportation Infrastructure Geotechnology (2025) Vol. 12, Iss. 2
Closed Access
A lightweight and explainable model to predict the dynamic normal stress on silo wall assisted with knowledge distillation
Zhijun Xu, Huijie Guo, Yongzhi Cheng, et al.
Powder Technology (2025), pp. 120753-120753
Closed Access
Prediction of hysteresis response of steel braces using long Short-Term memory artificial neural networks
Sepehr Pessiyan, Fardad Mokhtari, Ali Imanpour
Computers & Structures (2025) Vol. 309, pp. 107672-107672
Closed Access
Artificial Intelligence and Non-Destructive Testing Data to Assess Concrete Sustainability of Civil Engineering Infrastructures
Cédric Baudrit, Sylvain Dufau, Géraldine Villain, et al.
Materials (2025) Vol. 18, Iss. 4, pp. 826-826
Open Access
Performance characterisation of machine learning models for geotechnical axial pile load capacity estimation: an enhanced GPR-based approach
Ibrahim Haruna Umar, Mahir Sukairaj Salga, Hang Lin, et al.
Geomechanics and Geoengineering (2025), pp. 1-42
Closed Access
Modeling of the Uniaxial Compressive Strength of Carbonate Rocks Using Statistical Analysis and Artificial Neural Network
Mohammad Rasoul Setayeshirad, Ali Uromeie, Mohammad Reza Nikudel
Rock Mechanics and Rock Engineering (2025)
Closed Access
Data-driven reliability design of transverse impacted concrete-filled steel tube columns
Nan Xu, Yanhui Liu, Hongjin Chen, et al.
Thin-Walled Structures (2025), pp. 113163-113163
Closed Access
Shear strength parameters prediction of rock materials using hybrid machine learning model
Yanhui Cheng, Dongliang He, Hongwei Liu, et al.
Nondestructive Testing And Evaluation (2025), pp. 1-24
Closed Access
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