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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:

Experimental Study and Soft Computing Modeling of the Unconfined Compressive Strength of Limestone Rocks Considering Dry and Saturation Conditions
Saif Alzabeebee, Diyari Abdalrahman Mohammed, Younis M. Alshkane
Rock Mechanics and Rock Engineering (2022) Vol. 55, Iss. 9, pp. 5535-5554
Closed Access | Times Cited: 24

Showing 24 citing articles:

Intelligent Model for Dynamic Shear Modulus and Damping Ratio of Undisturbed Marine Clay Based on Back-Propagation Neural Network
Qi Wu, Zifan Wang, You Qin, et al.
Journal of Marine Science and Engineering (2023) Vol. 11, Iss. 2, pp. 249-249
Open Access | Times Cited: 20
Estimation of Intact Rock Uniaxial Compressive Strength Using Advanced Machine Learning
Jitendra Khatti, Kamaldeep Singh Grover
Transportation Infrastructure Geotechnology (2023) Vol. 11, Iss. 4, pp. 1989-2022
Closed Access | Times Cited: 19
Multiscale soft computing-based model of shear strength of steel fibre-reinforced concrete beams
Saif Alzabeebee, Rwayda Kh. S. Al‐Hamd, Ali Nassr, et al.
Innovative Infrastructure Solutions (2023) Vol. 8, Iss. 1
Open Access | Times Cited: 18
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: 18
Controlling factors in the variability of soil magnetic measures by machine learning and variable importance analysis
Kamran Azizi, Shamsollah Ayoubi, José Alexandre Melo Demattê
Journal of Applied Geophysics (2023) Vol. 210, pp. 104944-104944
Closed Access | Times Cited: 13
Finite element and evolutionary polynomial regression analyses of the effect of a cavity on the bearing capacity factor $${{\varvec{N}}}_{{\varvec{c}}}$$ of strip footing
Saif Alzabeebee, Bashar Ismael, Suraparb Keawsawasvong, et al.
Modeling Earth Systems and Environment (2024) Vol. 10, Iss. 3, pp. 3815-3826
Closed Access | Times Cited: 4
Comparative study on convolutional neural network and regression analysis to evaluate uniaxial compressive strength of Sandy Dolomite
Meiqian Wang, Wenlian Liu, Haiming Liu, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 4
Predicting uniaxial compressive strength of building stone based on index tests: Correlations, validity, reliability, and unification
Fanmeng Kong, Yiguo Xue, Junlong Shang, et al.
Construction and Building Materials (2024) Vol. 438, pp. 137227-137227
Closed Access | Times Cited: 4
Ion-Dependent Calcium Carbonate Cohesion: Insights from Surface Forces Measured between Calcite Surfaces
Joanna Dziadkowiec, Anja Røyne
Reviews in Mineralogy and Geochemistry (2025) Vol. 91A, Iss. 1, pp. 251-293
Closed Access
Probabilistic prediction of uniaxial compressive strength for rocks from sparse data using Bayesian Gaussian process regression with Synthetic Minority Oversampling Technique (SMOTE)
Chao Song, Tengyuan Zhao, Xu Ling, et al.
Computers and Geotechnics (2023) Vol. 165, pp. 105850-105850
Open Access | Times Cited: 12
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
Effective Machine-Learning Models for Rock Mass Deformation Modulus Estimation Based on Rock Mass Classification Systems
Mohammad Khajehzadeh, Suraparb Keawsawasvong, Mohammad Reza Motahari, et al.
Engineered Science (2024)
Open Access | Times Cited: 3
An Evolutionary Polynomial Computing of Pile Capacity Using the Results of High-strain Dynamic Test
Saif Alzabeebee, Bashar Ismael, Suraparb Keawsawasvong, et al.
Transportation Infrastructure Geotechnology (2024) Vol. 11, Iss. 5, pp. 3160-3177
Closed Access | Times Cited: 3
Developing soft-computing regression model for predicting bearing capacity of eccentrically loaded footings on anisotropic clay
Kongtawan Sangjinda, Rungkhun Banyong, Saif Alzabeebee, et al.
Artificial Intelligence in Geosciences (2023) Vol. 4, pp. 68-75
Open Access | Times Cited: 7
Soft Computing-Based Models for Estimating the Ultimate Bearing Capacity of an Annular Footing on Hoek–Brown Material
Suraparb Keawsawasvong, Kongtawan Sangjinda, Wittaya Jitchaijaroen, et al.
Arabian Journal for Science and Engineering (2023) Vol. 49, Iss. 4, pp. 5989-6006
Closed Access | Times Cited: 7
Machine Learning-Based Prediction of Shear Strength Parameters of Rock Materials
Dayong Han, Xinhua Xue
Rock Mechanics and Rock Engineering (2024) Vol. 57, Iss. 10, pp. 8795-8819
Closed Access | Times Cited: 2
Comparing 1D Regression and Evolutionary Polynomial Analyses for Predicting Brazilian Tensile Strength of Limestone in Dry and Saturated Conditions
Saif Alzabeebee, Younis M. Alshkane, Diyari Abdalrahman Mohammed, et al.
Geotechnical and Geological Engineering (2023) Vol. 42, Iss. 4, pp. 2495-2515
Closed Access | Times Cited: 5
Integrated machine learning for modeling bearing capacity of shallow foundations
Yuzhen Liu, Yan Liang
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 1
Developing some models to predict the uniaxial compressive strength of various sedimentary rocks (Case studies: large dam site and mine in Southeast China)
Zhe Wang, Zhou Zhou, Tao Sun, et al.
Case Studies in Construction Materials (2024) Vol. 21, pp. e03817-e03817
Open Access | Times Cited: 1
Efficient Machine Learning Models for the Uplift Behavior of Helical Anchors in Dense Sand for Wind Energy Harvesting
Le Wang, Mengting Wu, Hongzhen Chen, et al.
Applied Sciences (2022) Vol. 12, Iss. 20, pp. 10397-10397
Open Access | Times Cited: 7
Comparison of artificial intelligence and multivariate regression methods in predicting the uniaxial compressive strength of rock during the specific resistivity monitoring
Behnam Taghavi, Farnusch Hajizadeh, Hassan Moomivand
Bulletin of Engineering Geology and the Environment (2023) Vol. 82, Iss. 11
Closed Access | Times Cited: 3
Comparative Study on Convolutional Neural Network and Regression Analysis to Evaluate Uniaxial Compressive Strength of Sandy Dolomite
Wei Xu, Meiqian Wang, Wenlian Liu, et al.
Research Square (Research Square) (2024)
Open Access
Research on Rock Strength Prediction Model Based on Machine Learning Algorithm
Xiang Ding, Mengyun Dong, Wanqing Shen
Research Square (Research Square) (2024)
Open Access
Estimation of Uniaxial Strength of Rock: A Comparison between Bayesian-Optimized Machine Learning Models
Jitendra Khatti, Kamaldeep Singh Grover
Mining Metallurgy & Exploration (2024)
Closed Access
Research on rock strength prediction model based on machine learning algorithm
Xiang Ding, Mengyun Dong, Wanqing Shen
Deleted Journal (2024) Vol. 7, Iss. 1
Open Access
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