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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:

Machine Learning-Based Intelligent Prediction of Elastic Modulus of Rocks at Thar Coalfield
Niaz Muhammad Shahani, Xigui Zheng, Xiaowei Guo, et al.
Sustainability (2022) Vol. 14, Iss. 6, pp. 3689-3689
Open Access | Times Cited: 36

Showing 26-50 of 36 citing articles:

Hydro-mechanical coupling of rough fractures that exhibit dilatancy phenomena
Tianjiao Yang, A. P. S. Selvadurai, Pengyu Wang, et al.
Bulletin of Engineering Geology and the Environment (2022) Vol. 81, Iss. 10
Closed Access | Times Cited: 7
Framework for Bayesian Assessment of Factors that Impact Rock Mechanical Response
Zhidi Wu, Eric Edelman, Phil Smith, et al.
Rock Mechanics and Rock Engineering (2024) Vol. 57, Iss. 4, pp. 2961-2981
Closed Access | Times Cited: 1
A Comparative Study of Two Tree-Based Models for Predicting Flyrock Velocity at Open Pit Bench Mining
Ezatullah Rawnaq, Bassir Esmatyar, Akihiro Hamanaka, et al.
Open Journal of Applied Sciences (2024) Vol. 14, Iss. 02, pp. 267-287
Open Access | Times Cited: 1
Five Machine Learning Models Predicting the Global Shear Capacity of Composite Cellular Beams with Hollow-Core Units
Felipe Piana Vendramell Ferreira, Seong‐Hoon Jeong, Ehsan Mansouri, et al.
(2024)
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
Prediction of the effective properties of matrix composites via micromechanics-based machine learning
E. Polyzos
International Journal of Engineering Science (2024) Vol. 207, pp. 104184-104184
Closed Access | Times Cited: 1
Evaluation of Uniaxial Compressive Strength of Basalts using Machine Learning Methods and Comparison of Their Performances
N. Yesiloglu-Gultekin, Ayhan Doğan
Düzce Üniversitesi Bilim ve Teknoloji Dergisi (2023) Vol. 11, Iss. 2, pp. 1059-1074
Open Access | Times Cited: 1
Novel approaches in geomechanical parameter estimation using machine learning methods and conventional well logs
Farhad Mollaei, Ali Moradzadeh, Reza Mohebian
Geosystem Engineering (2024) Vol. 27, Iss. 5, pp. 252-277
Closed Access
Application of Machine Learning Models for Predicting Students' Performance in Mathematics: A K-Fold Approach
Felix Ale, Ikpaya D. Ikpaya, Ilesanmi Daniyan, et al.
(2024), pp. 1-9
Closed Access
Kohezyonlu zeminlerde net limit basınç ve deformasyon modülünün makine öğrenimi temelli modeller kullanılarak tahmin edilmesi
N. Yesiloglu-Gultekin, Ayhan Doğan
Ömer Halisdemir Üniversitesi Mühendislik Bilimleri Dergisi (2022)
Open Access | Times Cited: 1
Structure of Different Kinds of ANN Models
Mohammad Ehteram, Zohreh Sheikh Khozani, Saeed Soltani-Mohammadi, et al.
(2022), pp. 13-26
Closed Access | Times Cited: 1
QSPR study of viscoplastic properties of peptide-based hydrogels
Mostafa Montazeri, Mahsa Baghban Salehi, Babak Fazelabdolabadi, et al.
Journal of Biomolecular Structure and Dynamics (2023) Vol. 42, Iss. 13, pp. 6577-6587
Open Access
МЕТОДИ БУСТИНГОВОГО МАШИННОГО НАВЧАННЯ ДЛЯ НЕСТАЦІОНАРНИХ ЧАСОВИХ РЯДІВ
Христина ЛІП’ЯНІНА-ГОНЧАРЕНКО, Христина ЮРКІВ
Measuring and computing devices in technological processes (2023), Iss. 3, pp. 19-30
Open Access
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