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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 Compressive Strength of the Cement-Fly Ash–Slag Ternary Concrete Using the Firefly Algorithm (FA) and Random Forest (RF) Hybrid Machine-Learning Method
Jiandong Huang, Mohanad Muayad Sabri Sabri, Dmitrii Vladimirovich Ulrikh, et al.
Materials (2022) Vol. 15, Iss. 12, pp. 4193-4193
Open Access | Times Cited: 39

Showing 26-50 of 39 citing articles:

Predicting Microbiologically Influenced Concrete Corrosion in Self-cleansing Sewers using Meta-learning Techniques
Mohammad Zounemat‐Kermani, Ammar Aldallal
CORROSION (2024) Vol. 80, Iss. 4, pp. 338-348
Closed Access | Times Cited: 1
Multi-objective optimization of the flow condition of binary constituent net-zero concretes towards carbon neutrality-built environment pathway
César García, Kennedy C. Onyelowe, Paulina Elizabeth Valverde Aguirre, et al.
Journal of Building Pathology and Rehabilitation (2024) Vol. 9, Iss. 1
Closed Access | Times Cited: 1
Hybrid Machine Learning Model Based on GWO and PSO Optimization for Prediction of Oilwell Cement Compressive Strength under Acidic Corrosion
Lianzhou Wang, Sheng Huang, Zaoyuan Li, et al.
SPE Journal (2024) Vol. 29, Iss. 09, pp. 4684-4695
Closed Access | Times Cited: 1
Application of machine learning in predicting mechanical properties of sandcrete blocks made from quarry dust: a review
John Igeimokhia Braimah, Wasiu O. Ajagbe, Kolawole Adisa Olonade
AI in Civil Engineering (2024) Vol. 3, Iss. 1
Open Access | Times Cited: 1
Constitutive relations of nanoscale hydration products present in engineered cementitious composites from machine learning assisted experimental nanoindentation
S. Gautham, Saptarshi Sasmal
Journal of Building Engineering (2023) Vol. 75, pp. 106912-106912
Closed Access | Times Cited: 4
Ensemble learning models to predict the compressive strength of geopolymer concrete: a comparative study for geopolymer composition design
Qiong Tian, Zhanlin Su, Nicholas Fiorentini, et al.
Multiscale and Multidisciplinary Modeling Experiments and Design (2023) Vol. 7, Iss. 3, pp. 1793-1806
Closed Access | Times Cited: 4
A Comparative Study of AI-Based International Roughness Index (IRI) Prediction Models for Jointed Plain Concrete Pavement (JPCP)
Qiang Wang, Mengmeng Zhou, Mohanad Muayad Sabri Sabri, et al.
Materials (2022) Vol. 15, Iss. 16, pp. 5605-5605
Open Access | Times Cited: 7
Improvement of Computational Efficiency and Accuracy by Firefly Algorithm and Random Forest for Compressive Strength Modeling of Recycled Concrete
Yong Liu, Yang Wang, Mengmeng Zhou, et al.
Sustainability (2023) Vol. 15, Iss. 12, pp. 9170-9170
Open Access | Times Cited: 3
Evaluating 28-Days Performance of Rice Husk Ash Green Concrete under Compression Gleaned from Neural Networks
Sharanjit Singh, Harish Chandra Arora, Aman Kumar, et al.
Advances in Materials Science and Engineering (2023) Vol. 2023, pp. 1-18
Open Access | Times Cited: 2
Influence of Graphene Nanoplates on Dispersion, Hydration Behavior of Sulfoaluminate Cement Composites
Kai Cui, Jun Chang, Mohanad Muayad Sabri Sabri, et al.
Materials (2022) Vol. 15, Iss. 15, pp. 5357-5357
Open Access | Times Cited: 3
An Unbiased Fuzzy Weighted Relative Error Support Vector Machine for Reverse Prediction of Concrete Components
Zongwen Fan, Jin Gou, Shaoyuan Weng
IEEE Transactions on Artificial Intelligence (2024) Vol. 5, Iss. 9, pp. 4574-4584
Closed Access
Dingo optimization algorithm-based random forests model to evaluate the compressive strength of the concrete at elevated temperatures
Hongling Zhang, Hongzhi Zhang
Journal of Intelligent & Fuzzy Systems (2024), pp. 1-15
Closed Access
ML prediction and ANN-PSO based optimization for compressive strength of blended concrete
Mallikarjuna Reddy, Ramaprasad Reddy Lomada, C. Vivek Kumar, et al.
Cogent Engineering (2024) Vol. 11, Iss. 1
Open Access
Soft-Computing Analysis and Prediction of the Mechanical Properties of High-Volume Fly-Ash Concrete Containing Plastic Waste and Graphene Nanoplatelets
Musa Adamu, Yasser E. Ibrahim, Mahmud M. Jibril
Infrastructures (2024) Vol. 9, Iss. 12, pp. 214-214
Open Access
A Study on the Application of Machine Learning for Predicting Concrete Compressive Strength
Wanshun Jiang, Xiao Bing-gang, Yipeng Wang, et al.
(2023)
Open Access
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