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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:

Enhancing compressive strength prediction in self-compacting concrete using machine learning and deep learning techniques with incorporation of rice husk ash and marble powder
Muhammad Sarmad Mahmood, Ayub Elahi, Osama Zaid, et al.
Case Studies in Construction Materials (2023) Vol. 19, pp. e02557-e02557
Open Access | Times Cited: 17

Showing 17 citing articles:

High-Strength Self-Compacting Concrete Production Incorporating Supplementary Cementitious Materials: Experimental Evaluations and Machine Learning Modelling
Md. Habibur Rahman Sobuz, Fahim Shahriyar Aditto, Shuvo Dip Datta, et al.
International Journal of Concrete Structures and Materials (2024) Vol. 18, Iss. 1
Open Access | Times Cited: 12
Multi-performance optimization of low-carbon geopolymer considering mechanical, cost, and CO2 emission based on experiment and interpretable learning
Shiqi Wang, Keyu Chen, Jinlong Liu, et al.
Construction and Building Materials (2024) Vol. 425, pp. 136013-136013
Closed Access | Times Cited: 8
Analysis of Models to Predict Mechanical Properties of High-Performance and Ultra-High-Performance Concrete Using Machine Learning
Mohammad Hematibahar, Махмуд Харун, Alexey N. Beskopylny, et al.
Journal of Composites Science (2024) Vol. 8, Iss. 8, pp. 287-287
Open Access | Times Cited: 6
NSGA-II based short-term building energy management using optimal LSTM-MLP forecasts
Moisés Cordeiro-Costas, Hugo Labandeira-Pérez, Daniel Villanueva, et al.
International Journal of Electrical Power & Energy Systems (2024) Vol. 159, pp. 110070-110070
Open Access | Times Cited: 5
Utilization of Industrial, Agricultural, and Construction Waste in Cementitious Composites: A Comprehensive Review of their Impact on Concrete Properties and Sustainable Construction Practices.
Fahad Alsharari
Materials Today Sustainability (2025), pp. 101080-101080
Open Access
Prediction of mechanical properties of eco-friendly concrete using machine learning algorithms and partial dependence plot analysis
Tonmoy Roy, Pobithra Das, Ravi Jagirdar, et al.
Smart Construction and Sustainable Cities (2025) Vol. 3, Iss. 1
Open Access
Forecasting residual mechanical properties of hybrid fibre-reinforced self-compacting concrete (HFR-SCC) exposed to elevated temperatures
Waleed Bin Inqiad, Elena Valentina Dumitrascu, Robert Alexandru Dobre
Heliyon (2024) Vol. 10, Iss. 12, pp. e32856-e32856
Open Access | Times Cited: 4
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
Prediction and validation of mechanical properties of self-compacting geopolymer concrete using combined machine learning methods a comparative and suitability assessment of the best analysis
Kennedy C. Onyelowe, Ahmed M. Ebid, Paul O. Awoyera, et al.
Scientific Reports (2025) Vol. 15, Iss. 1
Open 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
Experimental assessment and hybrid machine learning-based feature importance analysis with the optimization of compressive strength of waste glass powder-modified concrete
Turki S. Alahmari, Md. Kawsarul Islam Kabbo, Md. Habibur Rahman Sobuz, et al.
Materials Today Communications (2025), pp. 112081-112081
Closed Access
Predicting residual strength of hybrid fibre-reinforced Self-compacting concrete (HFR-SCC) exposed to elevated temperatures using machine learning
Muhammad Saud Khan, Liqiang Ma, Waleed Bin Inqiad, et al.
Case Studies in Construction Materials (2024) Vol. 22, pp. e04112-e04112
Closed Access | Times Cited: 2
Deploying UAV-Based Detection of Bridge Structural Deterioration with Pilgrimage Walk Optimization-Lite for Computer Vision
Jui‐Sheng Chou, Chi‐Yun Liu, Pengyue Guo
Case Studies in Construction Materials (2024) Vol. 21, pp. e04048-e04048
Open Access | Times Cited: 1
Development of eco-friendly self-compacting concrete using marble powder, blast furnace slag and glass fibre-reinforced plastic waste: Application of mixture design approach
Manel Djeddou, Mohamed Amieur, Rabah Chaïd, et al.
Research on Engineering Structures and Materials (2024)
Open Access
Estimation on compressive strength of recycled aggregate self-compacting concrete using interpretable machine learning-based models
Suhang Yang, T. Chen, Zhifeng Xu
Engineering Computations (2024)
Closed Access
Metaheuristic-based machine learning approaches of compressive strength forecasting of steel fiber reinforced concrete with SHapley Additive exPlanations
Abul Kashem, Ayesha Anzer, Ravi Jagirdar, et al.
Multiscale and Multidisciplinary Modeling Experiments and Design (2024) Vol. 8, Iss. 1
Closed Access
Mechanical and Durability Properties of Coal Cinder Concrete: Experimental Study and GPR-Based Analysis
Al Toghrli, Seyed Azim Hosseini, Farshid Farokhizadeh
Case Studies in Construction Materials (2024), pp. e04093-e04093
Open Access
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