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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:

Closed-Form Equation for Estimating Unconfined Compressive Strength of Granite from Three Non-destructive Tests Using Soft Computing Models
Athanasia D. Skentou, Abidhan Bardhan, Anna Mamou, et al.
Rock Mechanics and Rock Engineering (2022) Vol. 56, Iss. 1, pp. 487-514
Open Access | Times Cited: 81

Showing 1-25 of 81 citing articles:

Analysis and prediction of the effect of Nanosilica on the compressive strength of concrete with different mix proportions and specimen sizes using various numerical approaches
Reyam Ali, Maryam Muayad, Ahmed Salih Mohammed, et al.
Structural Concrete (2022) Vol. 24, Iss. 3, pp. 4161-4184
Closed Access | Times Cited: 92
Multi-objective robust optimization for enhanced safety in large-diameter tunnel construction with interactive and explainable AI
Penghui Lin, Limao Zhang, Robert L. K. Tiong
Reliability Engineering & System Safety (2023) Vol. 234, pp. 109172-109172
Closed Access | Times Cited: 45
ANN-based swarm intelligence for predicting expansive soil swell pressure and compression strength
Fazal E. Jalal, Mudassir Iqbal, Waseem Akhtar Khan, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 31
Revealing the nature of soil liquefaction using machine learning
Sufyan Ghani, Ishwor Thapa, Amrendra Kumar, et al.
Earth Science Informatics (2025) Vol. 18, Iss. 2
Open Access | Times Cited: 3
Dimensionless Machine Learning: Dimensional Analysis to Improve LSSVM and ANN models and predict bearing capacity of circular foundations
Hongchao Li, Shahab Hosseini, Behrouz Gordan, et al.
Artificial Intelligence Review (2025) Vol. 58, Iss. 4
Open Access | Times Cited: 2
Developing bearing capacity model for geogrid-reinforced stone columns improved soft clay utilizing MARS-EBS hybrid method
Ali Reza Ghanizadeh, Afshin Ghanizadeh, Panagiotis G. Asteris, et al.
Transportation Geotechnics (2022) Vol. 38, pp. 100906-100906
Closed Access | Times Cited: 68
Modelling and validation of liquefaction potential index of fine-grained soils using ensemble learning paradigms
Sufyan Ghani, Sanjog Chhetri Sapkota, Raushan Kumar Singh, et al.
Soil Dynamics and Earthquake Engineering (2023) Vol. 177, pp. 108399-108399
Closed Access | Times Cited: 37
Several Tree-Based Solutions for Predicting Flyrock Distance Due to Mine Blasting
Mojtaba Yari, Danial Jahed Armaghani, Chrysanthos Maraveas, et al.
Applied Sciences (2023) Vol. 13, Iss. 3, pp. 1345-1345
Open Access | Times Cited: 31
Decision tree models for the estimation of geo-polymer concrete compressive strength
Ji Zhou, Zhanlin Su, Shahab Hosseini, et al.
Mathematical Biosciences & Engineering (2023) Vol. 21, Iss. 1, pp. 1413-1444
Open Access | Times Cited: 29
A Scientometrics Review of Soil Properties Prediction Using Soft Computing Approaches
Jitendra Khatti, Kamaldeep Singh Grover
Archives of Computational Methods in Engineering (2023) Vol. 31, Iss. 3, pp. 1519-1553
Closed Access | Times Cited: 24
Prediction of concrete compressive strength using support vector machine regression and non-destructive testing
Wanmao Zhang, Dunwen Liu, Kunpeng Cao
Case Studies in Construction Materials (2024) Vol. 21, pp. e03416-e03416
Open Access | Times Cited: 13
Assessment of Uniaxial Strength of Rocks: A Critical Comparison Between Evolutionary and Swarm Optimized Relevance Vector Machine Models
Jitendra Khatti, Kamaldeep Singh Grover
Transportation Infrastructure Geotechnology (2024) Vol. 11, Iss. 6, pp. 4098-4141
Closed Access | Times Cited: 13
Applying Optimized Machine Learning Models for Predicting Unconfined Compressive Strength in Fine-Grained Soil
Ishwor Thapa, Sufyan Ghani
Transportation Infrastructure Geotechnology (2024) Vol. 11, Iss. 4, pp. 2235-2269
Closed Access | Times Cited: 11
State-of-the-art review on the use of AI-enhanced computational mechanics in geotechnical engineering
Hongchen Liu, Huaizhi Su, Lizhi Sun, et al.
Artificial Intelligence Review (2024) Vol. 57, Iss. 8
Open Access | Times Cited: 9
Envisioning Human–Machine Relationship Towards Mining of the Future: An Overview
Peter Kolapo, Nafiu Olanrewaju Ogunsola, Kayode Komolafe, et al.
Mining (2025) Vol. 5, Iss. 1, pp. 5-5
Open Access | Times Cited: 1
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
Advanced Tree-Based Techniques for Predicting Unconfined Compressive Strength of Rock Material Employing Non-Destructive and Petrographic Tests
Yuzhen Wang, Mahdi Hasanipanah, Ahmad Safuan A. Rashid, et al.
Materials (2023) Vol. 16, Iss. 10, pp. 3731-3731
Open Access | Times Cited: 23
Machine learning-based model for the ultimate strength of circular concrete-filled fiber-reinforced polymer–steel composite tube columns
Kunting Miao, Zichao Pan, Airong Chen, et al.
Construction and Building Materials (2023) Vol. 394, pp. 132134-132134
Closed Access | Times Cited: 23
Prediction of the Uniaxial Compressive Strength of Rocks by Soft Computing Approaches
Reza Khajevand
Geotechnical and Geological Engineering (2023) Vol. 41, Iss. 6, pp. 3549-3574
Closed Access | Times Cited: 20
Optimized ANN-based approach for estimation of shear strength of soil
Ahsan Rabbani, Pijush Samui, Sunita Kumari
Asian Journal of Civil Engineering (2023) Vol. 24, Iss. 8, pp. 3627-3640
Closed Access | Times Cited: 20
Predictive Modeling of the Uniaxial Compressive Strength of Rocks Using an Artificial Neural Network Approach
Xin Wei, Niaz Muhammad Shahani, Xigui Zheng
Mathematics (2023) Vol. 11, Iss. 7, pp. 1650-1650
Open Access | Times Cited: 19
Uniaxial Compressive Strength Prediction for Rock Material in Deep Mine Using Boosting-Based Machine Learning Methods and Optimization Algorithms
Junjie Zhao, Diyuan Li, Jingtai Jiang, et al.
Computer Modeling in Engineering & Sciences (2024) Vol. 140, Iss. 1, pp. 275-304
Open Access | Times Cited: 8
Development of Z number-based fuzzy inference system to predict bearing capacity of circular foundations
Shahab Hosseini, Behrouz Gordan, Erol Kalkan
Artificial Intelligence Review (2024) Vol. 57, Iss. 6
Open Access | Times Cited: 7
Data-driven intelligent modeling of unconfined compressive strength of heavy metal-contaminated soil
Syed Taseer Abbas Jaffar, Xiangsheng Chen, Xiaohua Bao, et al.
Journal of Rock Mechanics and Geotechnical Engineering (2024)
Open Access | Times Cited: 7
Artificial intelligent techniques for prediction of rock strength and deformation properties – A review
Mujahid Ali, Sai Hin Lai
Structures (2023) Vol. 55, pp. 1542-1555
Closed Access | Times Cited: 16
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