Browsing by Author Pratheeba, J.
Showing results 1 to 17 of 17
| Issue Date | Title | Author(s) |
| 2023 | Characterization of the shape of aggregates using image analysis and machine learning classification tools | Daniel Niruban, S.; Mohan, S.; Pratheeba, J.; Sathushka, Heshan Bandara Wijekoon; Sathiparan, N. |
| 2023 | Characterization of the shape of aggregates using image analysis and machine learning classification tools | Daniel Niruban, S.; Sajeevan, M.; Pratheeba, J.; Sathushka Heshan, B.W.; Sathiparan, N. |
| 2022 | Comprehensive Machine Learning Analysis on the Phenotypes of COVID-19 Patients Using Transcription Data | Pratheeba, J. |
| 2023 | 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 | Sathiparan, N.; Pratheeba, J.; Daniel Niruban, S. |
| 2018 | INVESTIGATE THE POST WAR IMPROVEMENTS OF HYDRAULIC INFRASTRUCTURE IN IRRIGATION SYSTEMS OF KANAGARAYAN ARU RIVER BASIN USING HYDROLOGICAL MODEL | Janithra, S.; Pratheeba, J.; Athapattu, B.C.L.; Sampath, D.S.; Sivakumar, S.S. |
| 2023 | Investigation of Compaction on Compressive Strength and Porosity of Pervious Concrete | Sajeevan, M.; Daniel Niruban, S.; Rinduja, R.; Pratheeba, J. |
| 2023 | Predicting compressive strength of cementstabilized earth blocks using machine learning models incorporating cement content, ultrasonic pulse velocity, and electrical resistivity | Sathiparan, N.; Pratheeba, J. |
| 2023 | Prediction of compressive strength of fly ash blended pervious concrete: a machine learning approach | Sathiparan, N.; Pratheeba, J.; Daniel Niruban, S. |
| 2023 | Prediction of masonry prism strength using machine learning technique: Effect of dimension and strength parameters | Sathiparan, N.; Pratheeba, J. |
| 2022 | Prolonged viral shedding prediction on non-hospitalized, uncomplicated SARS-CoV-2 patients using their transcriptome data | Pratheeba, J. |
| 2023 | Protein data in the identification and stage prediction of bronchopulmonary dysplasia on preterm infants: a machine learning study | Pratheeba, J.; Bandara, K.M.D.D.; Nayanqjith, Y.G.A. |
| 2023 | Role of Different types of RNA molecules in the severity prediction of SARS-CoV - 2 patients. | Pratheeba, J. |
| 2023 | SARS-CoV-2 Diagnosis Using Transcriptome Data: A Machine Learning Approach | Pratheeba, J. |
| 2023 | Soft computing techniques to predict the compressive strength of groundnut shell ash-blended concrete | Sathiparan, N.; Pratheeba, J. |
| 2023 | Soft computing techniques to predict the electrical resistivity of pervious concrete | Daniel Niruban, S.; Pratheeba, J.; Sathiparan, N. |
| 2023 | Surface response regression and machine learning techniques to predict the characteristics of pervious concrete using non-destructive measurement: Ultrasonic pulse velocity and electrical resistivity | Sathiparan, N.; Pratheeba, J.; Daniel Niruban, S. |
| 2023 | Use of soft computing approaches for the prediction of compressive strength in concrete blends with eggshell powder | Sathiparan, N.; Pratheeba, J. |
