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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:

Artificial intelligence forecasting models of uniaxial compressive strength
Arsalan Mahmoodzadeh, Mokhtar Mohammadi, Hawkar Hashim Ibrahim, et al.
Transportation Geotechnics (2020) Vol. 27, pp. 100499-100499
Closed Access | Times Cited: 83

Showing 26-50 of 83 citing articles:

Machine learning-based modeling of interface creep behavior of grouted soil anchors with varying soil moistures
Genbao Zhang, Changjie Xu, Di Wang, et al.
Transportation Geotechnics (2024) Vol. 48, pp. 101299-101299
Closed Access | Times Cited: 5
Enhancing Hoek–Brown constant estimation accuracy based on rigidity index using deep neural network
Mohammad Sharghi, Mohammad Pirhooshyaran, Hoyoung Jeong
Geosciences Journal (2025)
Closed Access
Estimation of rock strength parameters from petrological contents using tree-based machine learning techniques
Javid Hussain, Xiaodong Fu, Jian Chen, et al.
AI in Civil Engineering (2025) Vol. 4, Iss. 1
Open 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
Prediction of CBR and resilient modulus of crushed waste rocks using machine learning models
Shengpeng Hao, Thomas Pabst
Acta Geotechnica (2022) Vol. 17, Iss. 4, pp. 1383-1402
Closed Access | Times Cited: 24
Optimal machine learning-based method for gauging compressive strength of nanosilica-reinforced concrete
Ibrahim Albaijan, Arsalan Mahmoodzadeh, Adil Hussein Mohammed, et al.
Engineering Fracture Mechanics (2023) Vol. 291, pp. 109560-109560
Closed Access | Times Cited: 15
Prediction of uniaxial compressive strength of rock based on lithology using stacking models
Zida Liu, Diyuan Li, Yongping Liu, et al.
Rock Mechanics Bulletin (2023) Vol. 2, Iss. 4, pp. 100081-100081
Open Access | Times Cited: 15
Failure node prediction study of in-service tunnel concrete for sulfate attack by PSO-LSTM based on Markov correction
Kunpeng Cao, Dunwen Liu, Yu Tang, et al.
Case Studies in Construction Materials (2024) Vol. 20, pp. e03153-e03153
Open Access | Times Cited: 4
Data-driven resilient model development and feature selection for rock compressive strength prediction using machine learning and transformer techniques
Md Mamunur Rahaman, Mohammad Islam Miah
Earth Science Informatics (2025) Vol. 18, Iss. 3
Closed Access
Prediction of Uniaxial Compressive Strength of Rock Via Genetic Algorithm—Selective Ensemble Learning
Huajin Zhang, Shunchuan Wu, Zhongxin Zhang
Natural Resources Research (2022) Vol. 31, Iss. 3, pp. 1721-1737
Closed Access | Times Cited: 20
Prediction of Strength and CBR Characteristics of Chemically Stabilized Coal Gangue: ANN and Random Forest Tree Approach
Muhammad Nasir Amin, Mudassir Iqbal, Mohammed Ashfaq, et al.
Materials (2022) Vol. 15, Iss. 12, pp. 4330-4330
Open Access | Times Cited: 20
Prediction of Uniaxial Compressive Strength in Rocks Based on Extreme Learning Machine Improved with Metaheuristic Algorithm
Junbo Qiu, Xin Yin, Yucong Pan, et al.
Mathematics (2022) Vol. 10, Iss. 19, pp. 3490-3490
Open Access | Times Cited: 19
Intelligent hybrid model to classify failure modes of overstressed rock masses in deep engineering
Zi-da Liu, Diyuan Li
Journal of Central South University (2023) Vol. 30, Iss. 1, pp. 156-174
Closed Access | Times Cited: 12
Comprehensive analysis of multiple machine learning techniques for rock slope failure prediction
Arsalan Mahmoodzadeh, Abed Alanazi, Adil Hussein Mohammed, et al.
Journal of Rock Mechanics and Geotechnical Engineering (2023) Vol. 16, Iss. 11, pp. 4386-4398
Open Access | Times Cited: 11
A stacked generalisation methodology for estimating the uniaxial compressive strength of rocks
Edmund Nana Asare, Michael Affam, Yao Yevenyo Ziggah
Smart Construction and Sustainable Cities (2023) Vol. 1, Iss. 1
Open Access | Times Cited: 10
Artificial intelligence in tunnel construction: A comprehensive review of hotspots and frontier topics
Lianbaichao Liu, Zhanping Song, Xu Li
Geohazard Mechanics (2023) Vol. 2, Iss. 1, pp. 1-12
Open Access | Times Cited: 10
The influence of crystal size of dolomite on engineering properties: a case study from the Rus Formation, Dammam Dome, Eastern Saudi Arabia
Ahmed Abd El Aal, Syed Haroon Ali, Ali Wahid, et al.
Bulletin of Engineering Geology and the Environment (2024) Vol. 83, Iss. 2
Closed Access | Times Cited: 3
Prediction of uniaxial compressive strength of rock samples using density weighted least squares twin support vector regression
Deepak Gupta, N. Natarajan
Neural Computing and Applications (2021) Vol. 33, Iss. 22, pp. 15843-15850
Closed Access | Times Cited: 25
A Comparative Study of Six Hybrid Prediction Models for Uniaxial Compressive Strength of Rock Based on Swarm Intelligence Optimization Algorithms
Yu Lei, Shengtao Zhou, Xuedong Luo, et al.
Frontiers in Earth Science (2022) Vol. 10
Open Access | Times Cited: 18
Soft Computing-Based Models for Predicting the Characteristic Impedance of Igneous Rock from Their Physico-mechanical Properties
Adeyemi Emman Aladejare, Toochukwu Ozoji, Abiodun Ismail Lawal, et al.
Rock Mechanics and Rock Engineering (2022) Vol. 55, Iss. 7, pp. 4291-4304
Open Access | Times Cited: 17
Application of Non-Destructive Test Results to Estimate Rock Mechanical Characteristics—A Case Study
Zhichun Fang, Jafar Qajar, Kosar Safari, et al.
Minerals (2023) Vol. 13, Iss. 4, pp. 472-472
Open Access | Times Cited: 10
Fast perception of rock mass strength and integrity in TBM tunnelling using in-situ penetration test
Weiqiang Xie, Xiao-Ping Zhang, Shao-Hui Tang, et al.
Tunnelling and Underground Space Technology (2023) Vol. 141, pp. 105358-105358
Closed Access | Times Cited: 9
Geopolymer-stabilized soils: influencing factors, strength development mechanism and sustainability
T. Vamsi Nagaraju, Sireesha Mantena, R. Gobinath, et al.
Journal of Taibah University for Science (2023) Vol. 17, Iss. 1
Open Access | Times Cited: 9
Application of Relationship model for the Measurement While Drilling Data to Predict Rock Uniaxial Compressive Strength for Tunneling
Ruijie Zhao, Shaoshuai Shi, Rubing Yao, et al.
Rock Mechanics and Rock Engineering (2024) Vol. 57, Iss. 9, pp. 7187-7203
Closed Access | Times Cited: 3
Application of a Hybrid Machine Learning Model for the Prediction of Compressive Strength and Elastic Modulus of Rocks
Xiaoliang Jin, Rui Zhao, Yulin Ma
Minerals (2022) Vol. 12, Iss. 12, pp. 1506-1506
Open Access | Times Cited: 14

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