Get started
Author

Pratheeba Jeyananthan

Observed names: J. Pratheeba, Jeyananthan Pratheeba, P. Jeyananthan
ORCID: 0000-0003-0476-3964
Observed ORCID: 0000-0003-0476-3964
OpenAlex ID: A5081921478
Surface response regression and machine learning techniques to predict the characteristics of pervious concrete using non-destructive measurement: Ultrasonic pulse velocity and electrical resistivity
2023 · Navaratnarajah Sathiparan, Pratheeba Jeyananthan, et al. · Measurement · 62
Prediction of masonry prism strength using machine learning technique: Effect of dimension and strength parameters
2023 · Navaratnarajah Sathiparan, Pratheeba Jeyananthan · Materials Today Communications · 52
Predicting compressive strength of cement-stabilized earth blocks using machine learning models incorporating cement content, ultrasonic pulse velocity, and electrical resistivity
2023 · Navaratnarajah Sathiparan, Pratheeba Jeyananthan · Nondestructive Testing And Evaluation · 42
Effect of aggregate size, aggregate to cement ratio and compaction energy on ultrasonic pulse velocity of pervious concrete: prediction by an analytical model and machine learning techniques
2023 · Navaratnarajah Sathiparan, Pratheeba Jeyananthan, et al. · Asian Journal of Civil Engineering · 35
Prediction of compressive strength of fly ash blended pervious concrete: a machine learning approach
2023 · Navaratnarajah Sathiparan, Pratheeba Jeyananthan, et al. · International Journal of Pavement Engineering · 34
Predicting compressive strength of quarry waste-based geopolymer mortar using machine learning algorithms incorporating mix design and ultrasonic pulse velocity
2024 · Navaratnarajah Sathiparan, Pratheeba Jeyananthan · Nondestructive Testing And Evaluation · 22
Soft computing techniques to predict the electrical resistivity of pervious concrete
2023 · Daniel Niruban Subramaniam, Pratheeba Jeyananthan, et al. · Asian Journal of Civil Engineering · 22
Predicting compressive strength of pervious concrete with fly ash: a machine learning approach and analysis of fly ash compositional influence
2024 · Navaratnarajah Sathiparan, Pratheeba Jeyananthan, et al. · Multiscale and Multidisciplinary Modeling Experiments and Design · 20
Silica fume as a supplementary cementitious material in pervious concrete: prediction of compressive strength through a machine learning approach
2024 · Navaratnarajah Sathiparan, Pratheeba Jeyananthan, et al. · Asian Journal of Civil Engineering · 20
Investigation of Compaction on Compressive Strength and Porosity of Pervious Concrete
2023 · M. Sajeevan, D. N. Subramaniam, et al. · International Journal of Pavement Research and Technology · 19
A machine learning approach to predicting pervious concrete properties: a review
2025 · Navaratnarajah Sathiparan, Pratheeba Jeyananthan, et al. · Innovative Infrastructure Solutions · 18
A comparative study of machine learning techniques and data processing for predicting the compressive strength of pervious concrete with supplementary cementitious materials and chemical composition influence
2025 · Navaratnarajah Sathiparan, Pratheeba Jeyananthan, et al. · Next Materials · 16
Machine learning techniques to evaluate the impact of calcium oxide (CaO) and silicon dioxide (SiO2) in supplementary cement materials on the compressive strength of sustainable pervious concrete
2024 · Navaratnarajah Sathiparan, Pratheeba Jeyananthan, et al. · Sustainable Chemistry and Pharmacy · 15
Soft computing to predict the porosity and permeability of pervious concrete based on mix design and ultrasonic pulse velocity
2024 · Navaratnarajah Sathiparan, Sathushka Heshan Wijekoon, et al. · International Journal of Pavement Engineering · 13
Prediction of moisture content of cement-stabilized earth blocks using soil characteristics, cement content, and ultrasonic pulse velocity
2024 · Navaratnarajah Sathiparan, R. A. N. S. Tharuka, et al. · Journal of Engineering and Applied Science · 12
PDF
Characterization of the shape of aggregates using image analysis and machine learning classification tools
2023 · Daniel Niruban Subramaniam, Mohan Sajeevan, et al. · Geomechanics and Geoengineering · 12
Influence of metakaolin on pervious concrete strength: a machine learning approach with shapley additive explanations
2024 · Navaratnarajah Sathiparan, Pratheeba Jeyananthan, et al. · Multiscale and Multidisciplinary Modeling Experiments and Design · 11
Response surface regression and machine learning models to predict the porosity and compressive strength of pervious concrete based on mix design parameters
2024 · Navaratnarajah Sathiparan, Sathushka Heshan Wijekoon, et al. · Road Materials and Pavement Design · 10
Machine learning in the identification of phenotypes of multiple sclerosis patients
2024 · Pratheeba Jeyananthan · International Journal of Information Technology · 10
Soft computing techniques to predict the compressive strength of groundnut shell ash-blended concrete
2023 · Navaratnarajah Sathiparan, Pratheeba Jeyananthan · Journal of Engineering and Applied Science · 9
PDF
SARS-CoV-2 Diagnosis Using Transcriptome Data: A Machine Learning Approach
2023 · Pratheeba Jeyananthan · SN Computer Science · 9
PDF
Prediction of characteristics of pervious concrete by machine learning technique using mix parameters and non-destructive test measurements
2025 · Navaratnarajah Sathiparan, Sathushka Heshan Wijekoon, et al. · Nondestructive Testing And Evaluation · 8
Investigation of impact of aggregate shape on pervious concrete using machine learning classification methods
2025 · Sathushka Heshan Bandara Wijekoon, Navakulan Ahilash, et al. · Engineering Applications of Artificial Intelligence · 8
Protein data in the identification and stage prediction of bronchopulmonary dysplasia on preterm infants: a machine learning study
2023 · Pratheeba Jeyananthan, K. M. D. D. Bandara, et al. · International Journal of Information Technology · 8
Role of different types of RNA molecules in the severity prediction of SARS-CoV-2 patients
2023 · Pratheeba Jeyananthan · Pathology - Research and Practice · 8
PDF
Works count: 46
Citation count: 543
H-index: 13
I10-index: 19
Year
Topic
Type