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:
Compressive strength prediction of ternary blended geopolymer concrete using artificial neural networks and support vector regression
K. K. Yaswanth, Veerappan Sathish Kumar, J. Revathy, et al.
Innovative Infrastructure Solutions (2024) Vol. 9, Iss. 2
Closed Access | Times Cited: 12
K. K. Yaswanth, Veerappan Sathish Kumar, J. Revathy, et al.
Innovative Infrastructure Solutions (2024) Vol. 9, Iss. 2
Closed Access | Times Cited: 12
Showing 12 citing articles:
Modeling green recycled aggregate concrete using machine learning and variance-based sensitivity analysis
Mahmoud Owais, Lamiaa K. Idriss
Construction and Building Materials (2024) Vol. 440, pp. 137393-137393
Closed Access | Times Cited: 11
Mahmoud Owais, Lamiaa K. Idriss
Construction and Building Materials (2024) Vol. 440, pp. 137393-137393
Closed Access | Times Cited: 11
Comprehensive study of eccentrically loaded CFRP-confined RC columns maximum capacity: prediction via ANN and GEP
Hassan Sabetifar, Maryam Fakhari, Moein Nikofar, et al.
Multiscale and Multidisciplinary Modeling Experiments and Design (2025) Vol. 8, Iss. 3
Closed Access | Times Cited: 1
Hassan Sabetifar, Maryam Fakhari, Moein Nikofar, et al.
Multiscale and Multidisciplinary Modeling Experiments and Design (2025) Vol. 8, Iss. 3
Closed Access | Times Cited: 1
A critical analysis of compressive strength prediction of glass fiber and carbon fiber reinforced concrete over machine learning models
K. K. Yaswanth, V. S. Vani, Krupasindhu Biswal, et al.
Multiscale and Multidisciplinary Modeling Experiments and Design (2025) Vol. 8, Iss. 3
Closed Access | Times Cited: 1
K. K. Yaswanth, V. S. Vani, Krupasindhu Biswal, et al.
Multiscale and Multidisciplinary Modeling Experiments and Design (2025) Vol. 8, Iss. 3
Closed Access | Times Cited: 1
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: 7
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: 7
Usage of machine learning methods for forecasting the strength of environmentally friendly geopolymer concrete
Sheng Wang, Yulai Cong, Xin’e Yan
Journal of Ambient Intelligence and Humanized Computing (2025)
Closed Access
Sheng Wang, Yulai Cong, Xin’e Yan
Journal of Ambient Intelligence and Humanized Computing (2025)
Closed Access
Compatibility of sustainable geopolymer based on artificial neural network
Prajjwal Prabhakar, Rohit Kumar
Innovative Infrastructure Solutions (2024) Vol. 9, Iss. 8
Closed Access | Times Cited: 2
Prajjwal Prabhakar, Rohit Kumar
Innovative Infrastructure Solutions (2024) Vol. 9, Iss. 8
Closed Access | Times Cited: 2
Harnessing explainable artificial intelligence (XAI) for enhanced geopolymer concrete mix optimization
Bh Revathi, R. Gobinath, Govindasamy Bala, et al.
Results in Engineering (2024), pp. 103036-103036
Open Access | Times Cited: 2
Bh Revathi, R. Gobinath, Govindasamy Bala, et al.
Results in Engineering (2024), pp. 103036-103036
Open Access | Times Cited: 2
Deep learning based damage detection of concrete structures
Maheswara Rao Bandi, Laxmi Narayana Pasupuleti, T. K. Das, et al.
Asian Journal of Civil Engineering (2024) Vol. 25, Iss. 7, pp. 5197-5204
Closed Access | Times Cited: 1
Maheswara Rao Bandi, Laxmi Narayana Pasupuleti, T. K. Das, et al.
Asian Journal of Civil Engineering (2024) Vol. 25, Iss. 7, pp. 5197-5204
Closed Access | Times Cited: 1
Neural Network Prediction and Enhanced Strength Properties of Natural Fibre-Reinforced Quaternary-Blended Composites
Pavithra Chandramouli, Mohamed Riyaaz Nayum Akthar, Veerappan Sathish Kumar, et al.
CivilEng (2024) Vol. 5, Iss. 4, pp. 827-851
Open Access | Times Cited: 1
Pavithra Chandramouli, Mohamed Riyaaz Nayum Akthar, Veerappan Sathish Kumar, et al.
CivilEng (2024) Vol. 5, Iss. 4, pp. 827-851
Open Access | Times Cited: 1
Analysis and prediction of compressive strength of calcium aluminate cement paste based on machine learning
Bin Yang, Ji Ping Hao, Jiale Shen, et al.
Archives of Civil and Mechanical Engineering (2024) Vol. 25, Iss. 1
Closed Access | Times Cited: 1
Bin Yang, Ji Ping Hao, Jiale Shen, et al.
Archives of Civil and Mechanical Engineering (2024) Vol. 25, Iss. 1
Closed Access | Times Cited: 1
A novel composite machine learning model for the prediction of compressive strength of blended concrete
Elluri Venkata Prasad, S. Rama Krishna, Sudhakar Singha
Journal of Building Pathology and Rehabilitation (2024) Vol. 10, Iss. 1
Closed Access
Elluri Venkata Prasad, S. Rama Krishna, Sudhakar Singha
Journal of Building Pathology and Rehabilitation (2024) Vol. 10, Iss. 1
Closed Access
Feasibility study of novel Bengal Gram Husk Ash as a supplementary cementitious material: mechanical, durabilty and microstructural assessments
K. K. Yaswanth, Gaurav Kumar, V. S. Vani, et al.
Multiscale and Multidisciplinary Modeling Experiments and Design (2024) Vol. 8, Iss. 1
Closed Access
K. K. Yaswanth, Gaurav Kumar, V. S. Vani, et al.
Multiscale and Multidisciplinary Modeling Experiments and Design (2024) Vol. 8, Iss. 1
Closed Access
