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 compressive strength of quarry waste-based geopolymer mortar using machine learning algorithms incorporating mix design and ultrasonic pulse velocity
Navaratnarajah Sathiparan, Pratheeba Jeyananthan
Nondestructive Testing And Evaluation (2024) Vol. 39, Iss. 8, pp. 2486-2509
Closed Access | Times Cited: 10
Navaratnarajah Sathiparan, Pratheeba Jeyananthan
Nondestructive Testing And Evaluation (2024) Vol. 39, Iss. 8, pp. 2486-2509
Closed Access | Times Cited: 10
Showing 10 citing articles:
Utilizing an enhanced machine learning approach for geopolymer concrete analysis
Diksha Diksha, Nirendra Dev, Pradeep Goyal
Nondestructive Testing And Evaluation (2024), pp. 1-28
Closed Access | Times Cited: 5
Diksha Diksha, Nirendra Dev, Pradeep Goyal
Nondestructive Testing And Evaluation (2024), pp. 1-28
Closed Access | Times Cited: 5
Predicting the strength of alkali-activated masonry blocks using machine learning models: geopolymer mortar with quarry waste, rice husk ash, and eggshell ash
Anis Ahamed, S. Sakeek Yamani, L. S. Dissanayaka, et al.
Journal of Building Pathology and Rehabilitation (2025) Vol. 10, Iss. 1
Closed Access
Anis Ahamed, S. Sakeek Yamani, L. S. Dissanayaka, et al.
Journal of Building Pathology and Rehabilitation (2025) Vol. 10, Iss. 1
Closed Access
Prediction of characteristics of pervious concrete by machine learning technique using mix parameters and non-destructive test measurements
Navaratnarajah Sathiparan, Sathushka Heshan Bandara Wijekoon, Pratheeba Jeyananthan, et al.
Nondestructive Testing And Evaluation (2025), pp. 1-50
Closed Access
Navaratnarajah Sathiparan, Sathushka Heshan Bandara Wijekoon, Pratheeba Jeyananthan, et al.
Nondestructive Testing And Evaluation (2025), pp. 1-50
Closed Access
Predicting corrosion behaviour of steel reinforcement in eco-friendly coral aggregate concrete based on hybrid machine learning methods
Zhen Sun, Yalin Li, Li Su, et al.
Nondestructive Testing And Evaluation (2024), pp. 1-21
Closed Access | Times Cited: 4
Zhen Sun, Yalin Li, Li Su, et al.
Nondestructive Testing And Evaluation (2024), pp. 1-21
Closed 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
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
Predicting compressive strength of pervious concrete with fly ash: a machine learning approach and analysis of fly ash compositional influence
Navaratnarajah Sathiparan, Pratheeba Jeyananthan, Daniel Niruban Subramaniam
Multiscale and Multidisciplinary Modeling Experiments and Design (2024) Vol. 7, Iss. 6, pp. 5651-5671
Closed Access | Times Cited: 3
Navaratnarajah Sathiparan, Pratheeba Jeyananthan, Daniel Niruban Subramaniam
Multiscale and Multidisciplinary Modeling Experiments and Design (2024) Vol. 7, Iss. 6, pp. 5651-5671
Closed Access | Times Cited: 3
Data-driven models to predict the water-to-cement ratio and initial setting time of cement grouts
Jiahe Liu, Li Tang, Dongsheng Li, et al.
Nondestructive Testing And Evaluation (2024), pp. 1-20
Closed Access | Times Cited: 2
Jiahe Liu, Li Tang, Dongsheng Li, et al.
Nondestructive Testing And Evaluation (2024), pp. 1-20
Closed Access | Times Cited: 2
Response surface regression and machine learning models to predict the porosity and compressive strength of pervious concrete based on mix design parameters
Navaratnarajah Sathiparan, Sathushka Heshan Bandara Wijekoon, Rinduja Ravi, et al.
Road Materials and Pavement Design (2024), pp. 1-40
Closed Access | Times Cited: 1
Navaratnarajah Sathiparan, Sathushka Heshan Bandara Wijekoon, Rinduja Ravi, et al.
Road Materials and Pavement Design (2024), pp. 1-40
Closed Access | Times Cited: 1
Prediction of Characteristics of Pervious Concrete by Machine Learning Technique Using Mix Parameters and Non-destructive Test Measurements
Navaratnarajah Sathiparan, Pratheeba Jeyananthan, Sathushka Heshan Bandara Wijekoon, et al.
Research Square (Research Square) (2024)
Open Access
Navaratnarajah Sathiparan, Pratheeba Jeyananthan, Sathushka Heshan Bandara Wijekoon, et al.
Research Square (Research Square) (2024)
Open Access
Prediction of moisture content of cement-stabilized earth blocks using soil characteristics, cement content, and ultrasonic pulse velocity
Navaratnarajah Sathiparan, R. A. N. S. Tharuka, Pratheeba Jeyananthan
Journal of Engineering and Applied Science (2024) Vol. 71, Iss. 1
Open Access
Navaratnarajah Sathiparan, R. A. N. S. Tharuka, Pratheeba Jeyananthan
Journal of Engineering and Applied Science (2024) Vol. 71, Iss. 1
Open Access
