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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 the uniaxial compressive strength of oil palm shell lightweight aggregate concrete using artificial intelligence‐based algorithms
Weixiang Zhu, Lihua Huang, Liudan Mao, et al.
Structural Concrete (2021) Vol. 23, Iss. 6, pp. 3631-3650
Closed Access | Times Cited: 33

Showing 1-25 of 33 citing articles:

Predicting resilient modulus of flexible pavement foundation using extreme gradient boosting based optimised models
Reza Sarkhani Benemaran, Mahzad Esmaeili‐Falak, Akbar A. Javadi
International Journal of Pavement Engineering (2022) Vol. 24, Iss. 2
Open Access | Times Cited: 83
Application of extreme gradient boosting method for evaluating the properties of episodic failure of borehole breakout
Reza Sarkhani Benemaran
Geoenergy Science and Engineering (2023) Vol. 226, pp. 211837-211837
Closed Access | Times Cited: 57
Improved arithmetic optimization algorithm and its application to carbon fiber reinforced polymer-steel bond strength estimation
Xiaoling Shi, Xinping Yu, Mahzad Esmaeili‐Falak
Composite Structures (2022) Vol. 306, pp. 116599-116599
Closed Access | Times Cited: 62
General and optimal 2D convolutional neural networks to predict the residual compressive strength of concretes exposed to high temperatures
Hamed Kharrazi, Vahab Toufigh, Mehrdad Boroushaki
Engineering Applications of Artificial Intelligence (2024) Vol. 131, pp. 107901-107901
Closed Access | Times Cited: 11
Retracted: A comparative study on predicting the rapid chloride permeability of self‐compacting concrete using meta‐heuristic algorithm and artificial intelligence techniques
Yuan Jia, Ming Zhao, Mahzad Esmaeili‐Falak
Structural Concrete (2022) Vol. 23, Iss. 2, pp. 753-774
Closed Access | Times Cited: 36
Retracted: Predicting the compressive strength of modified recycled aggregate concrete
Cuina Yang, Hongwei Feng, Mahzad Esmaeili‐Falak
Structural Concrete (2022) Vol. 23, Iss. 6, pp. 3696-3717
Closed Access | Times Cited: 30
Fly ash-based geopolymer concrete's compressive strength estimation by applying artificial intelligence methods
Gholamreza Pazouki
Measurement (2022) Vol. 203, pp. 111916-111916
Closed Access | Times Cited: 29
Artificial intelligence techniques in advanced concrete technology: A comprehensive survey on 10 years research trend
Ramin Kazemi
Engineering Reports (2023) Vol. 5, Iss. 9
Open Access | Times Cited: 21
Reinforcing effect of CNT on the microstructure and creep properties of high-strength lightweight concrete
Se-Hee Hong, Jin-Seok Choi, Sun-Jae Yoo, et al.
Construction and Building Materials (2024) Vol. 428, pp. 136294-136294
Closed Access | Times Cited: 8
XGB-Northern Goshawk Optimization: Predicting the Compressive Strength of Self-Compacting Concrete
Jiang Bian, Ruili Huo, Yan Zhong, et al.
KSCE Journal of Civil Engineering (2024) Vol. 28, Iss. 4, pp. 1423-1439
Open Access | Times Cited: 7
An interpretable probabilistic machine learning model for forecasting compressive strength of oil palm shell-based lightweight aggregate concrete containing fly ash or silica fume
Yang‐Kook Sun, Han‐Seung Lee
Construction and Building Materials (2024) Vol. 426, pp. 136176-136176
Closed Access | Times Cited: 6
Prediction and uncertainty quantification of compressive strength of high‐strength concrete using optimized machine learning algorithms
Bing Han, Yanqi Wu, Lulu Liu
Structural Concrete (2022) Vol. 23, Iss. 6, pp. 3772-3785
Closed Access | Times Cited: 27
An effective chaotic maps image encryption based on metaheuristic optimizers
Sally Mohamed Sameh, Hossam El-Din Moustafa, Ehab H. Abdelhay, et al.
The Journal of Supercomputing (2023) Vol. 80, Iss. 1, pp. 141-201
Closed Access | Times Cited: 9
Prediction of the compressive strength of self‐compacting concrete using artificial neural networks based on rheological parameters
Yousef El Asri, Mouhcine Benaicha, Mounir Zaher, et al.
Structural Concrete (2022) Vol. 23, Iss. 6, pp. 3864-3876
Open Access | Times Cited: 14
Efficient mix design method for lightweight high strength concrete: A machine learning approach
Mohamed Sifan, Hoang X. Nguyen, Brabha Nagaratnam, et al.
Structures (2023) Vol. 55, pp. 1805-1822
Closed Access | Times Cited: 8
Advanced soft computing techniques for predicting punching shear strength
Minh-Tu Cao
Journal of Building Engineering (2023) Vol. 79, pp. 107800-107800
Closed Access | Times Cited: 7
Evaluation of compressive strength of the HPC produced with admixtures by a novel hybrid SVR model
Xiaoxuan Hu
Multiscale and Multidisciplinary Modeling Experiments and Design (2023) Vol. 6, Iss. 3, pp. 357-370
Closed Access | Times Cited: 7
Comparison of regression analysis for estimation of initial and total fracture energy of concrete
Jia Peng
Multiscale and Multidisciplinary Modeling Experiments and Design (2023) Vol. 7, Iss. 1, pp. 173-190
Closed Access | Times Cited: 6
Innovative lightweight concrete: effect of fiber, bacteria and nanomaterials
Hatice Elif Beytekin, Öznur Biricik Altun, Ali Mardani, et al.
Iranian Polymer Journal (2024) Vol. 33, Iss. 9, pp. 1327-1350
Open Access | Times Cited: 2
A comparative study of normal and self-compacting geopolymer mortar and its strength prediction using tensor flow approach
P.J. Ardhira, Dhanya Sathyan
Materials Today Proceedings (2022) Vol. 65, pp. 1046-1055
Closed Access | Times Cited: 9
Predict the properties of self-compacting concrete using the optimized support vector regression models
Jie Li, Gongxing Yan, Haojie Chen
Multiscale and Multidisciplinary Modeling Experiments and Design (2023) Vol. 6, Iss. 3, pp. 431-450
Closed Access | Times Cited: 4
Comparison of SVR models for predicting the compaction properties of lateritic soils as novel hybrid methods
Pengyu Zhu, Ye Zhu, Peng Zhang
Engineering Research Express (2022) Vol. 4, Iss. 3, pp. 035038-035038
Closed Access | Times Cited: 5
Compressive strength estimation of ultra-great workability concrete using hybrid algorithms
Yongcun Zhang, Zhe Bai, Huiping Zhang
Multiscale and Multidisciplinary Modeling Experiments and Design (2023) Vol. 6, Iss. 3, pp. 389-400
Closed Access | Times Cited: 2
Evaluation of Standard Compaction Parameters of Lateritic Soils Using Regression Analysis
Peng Yao, Mengyang Lu
International Journal of Geosynthetics and Ground Engineering (2023) Vol. 9, Iss. 3
Closed Access | Times Cited: 2
Retracted: Application of optimization‐based estimation analysis for predicting the compressive strength of eco‐friendly modified geopolymer concrete
Jin Jian-qing, Tongge Wu, Zhijun Zhang, et al.
Structural Concrete (2022)
Closed Access | Times Cited: 3
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