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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:

Deep learning based concrete compressive strength prediction model with hybrid meta-heuristic approach
Deepa A. Joshi, Radhika Menon, R.K. Jain, et al.
Expert Systems with Applications (2023) Vol. 233, pp. 120925-120925
Closed Access | Times Cited: 19

Showing 19 citing articles:

Efficient compressive strength prediction of concrete incorporating recycled coarse aggregate using Newton’s boosted backpropagation neural network (NB-BPNN)
Rupesh Kumar Tipu, Vandna Batra, Suman Suman, et al.
Structures (2023) Vol. 58, pp. 105559-105559
Closed Access | Times Cited: 22
Coupled extreme gradient boosting algorithm with artificial intelligence models for predicting compressive strength of fiber reinforced polymer- confined concrete
Tao Hai, Zainab Hasan Ali, Faisal M. Mukhtar, et al.
Engineering Applications of Artificial Intelligence (2024) Vol. 134, pp. 108674-108674
Closed Access | Times Cited: 8
Predicting Mechanical Properties of Concrete Structures Using Metaheuristic-Optimization-Based Machine Learning Models
Ngoc‐Mai Nguyen
Applied Soft Computing (2025), pp. 112893-112893
Closed Access
Intelligent Prediction of Compressive Strength of Concrete Based on CNN-BiLSTM-MA
Yuqiao Liu, Hongling Yu, Tao Guan, et al.
Case Studies in Construction Materials (2025), pp. e04486-e04486
Open Access
Strength prediction of recycled concrete using hybrid artificial intelligence models with Gaussian noise addition
Yaqin Geng, Yongcheng Ji, Dayang Wang, et al.
Engineering Applications of Artificial Intelligence (2025) Vol. 149, pp. 110566-110566
Closed Access
Integrated deep learning and Bayesian optimization approach for enhanced prediction of high-performance concrete strength
Rupesh Kumar Tipu, Archna Goyal, Digvijay Singh, et al.
Asian Journal of Civil Engineering (2025)
Closed Access
A systematic literature review of AI-based prediction methods for self-compacting, geopolymer, and other eco-friendly concrete types: Advancing sustainable concrete
Tariq Ali, Mohamed Hechmi El Ouni, Muhammad Zeeshan Qureshi, et al.
Construction and Building Materials (2024) Vol. 440, pp. 137370-137370
Closed Access | Times Cited: 4
A machine learning framework for predicting shear strength properties of rock materials
Daxing Lei, Yaoping Zhang, Zhigang Lu, et al.
Scientific Reports (2025) Vol. 15, Iss. 1
Open Access
Machine learning-guided optimization of coarse aggregate mix proportion based on CO2 intensity index
Yi Liu, Jiaoling Zhang, Suhui Zhang, et al.
Journal of CO2 Utilization (2024) Vol. 85, pp. 102862-102862
Open Access | Times Cited: 3
Supervised data-driven approach to predict split tensile and flexural strength of concrete with marble waste powder
Pala Ravikanth, T. Jothi Saravanan, K.I. Syed Ahmed Kabeer
Cleaner Materials (2024) Vol. 11, pp. 100231-100231
Open Access | Times Cited: 2
The local information extraction BFRC compressive strength prediction method via one-dimensional convolutional residual network
Hong Li, Zhouhong Zong, Jiajian Lin, et al.
Materials Today Communications (2024) Vol. 39, pp. 108834-108834
Closed Access | Times Cited: 2
Enhanced Prediction and Evaluation of Hydraulic Concrete Compressive Strength Using Multiple Soft Computing and Metaheuristic Optimization Algorithms
Tianyu Li, Xiamin Hu, Tao Li, et al.
Buildings (2024) Vol. 14, Iss. 11, pp. 3461-3461
Open Access | Times Cited: 1
Microstructure-Informed Deep Learning Model for Accurate Prediction of Multiple Concrete Properties
Ye Li, Yiming Ma, Kang Hai Tan, et al.
Journal of Building Engineering (2024) Vol. 98, pp. 111339-111339
Closed Access | Times Cited: 1
Lightweight Bi-LSTM method for the prediction of mechanical properties of concrete
Mrinal Anand, M. Anand, Minwoong Joe, et al.
Multimedia Tools and Applications (2023) Vol. 83, Iss. 18, pp. 54863-54884
Closed Access | Times Cited: 2
Optimizing compressive strength prediction using adversarial learning and hybrid regularization
Tamoor Aziz, Haroon Aziz, Srijidtra Mahapakulchai, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access
A heuristic approach of modelling developing countries' construction sector uncertainties to improve the building environment
Ursula Joyce Merveilles Pettang Nana, Cédric Cabral Fandjio Yonzou, Patrick Joël Mbiada Mbiada, et al.
Frontiers in Built Environment (2024) Vol. 10
Open Access
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
A scientometric analysis on self-curing, self-compacting and self-healing concrete
S. Vijaymurugan, K. Poongodi, P. Murthi
AIP conference proceedings (2024) Vol. 3122, pp. 070017-070017
Closed Access
Comparative strength estimation model of recycled aggregate concrete modified with GGBS, Metakaolin, and fly ash
Lina Zhang, Yuqing Tian, Shan Deng
Multiscale and Multidisciplinary Modeling Experiments and Design (2024) Vol. 7, Iss. 6, pp. 5461-5479
Closed Access
An energy-aware migration framework using metaheuristic algorithm in cloud computing
Saurabh Singhal, Ashish Sharma
Knowledge and Information Systems (2024) Vol. 67, Iss. 2, pp. 1373-1398
Closed Access
Compressive strength prediction of high-performance concrete: Integrating multi-ingredient influences and mix proportion insights
Qingqing Chen, Jie Zhang, Linghao Zhang, et al.
Construction and Building Materials (2024) Vol. 451, pp. 138791-138791
Closed Access
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