Imesh Udara Ekanayake

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D. P. P. MeddageUniversity of New South Wales, AustraliaVerified email at ad.unsw.edu.au
Upaka RathnayakeProfessor, Atlantic Technological University, Sligo IrelandVerified email at atu.ie
C. S. LewangamageProfessor, Department of Civil Engineering, University of MoratuwaVerified email at uom.lk
A. U. WeerasuriyaHong Kong Metropolitan UniversityVerified email at hkmu.edu.hk
Udara Sachinthana PereraLecturer, Faculty of Engineering, Sri Lanka Institute of Information Technology – SLIITVerified email at sliit.lk
Damayanthi HerathUniversity of PeradeniyaVerified email at eng.pdn.ac.lk
K.T. TseThe Hong Kong University of Science and TechnologyVerified email at ust.hk
Tharindu Pradeeptha MiyanawalaScientistVerified email at tcoms.sg
Dr Chamil Erik RamanayakaLecturer, Central Queensland UniversityVerified email at cqu.edu.au
Mohammad Azamathulla HaziThe University of the West IndiesVerified email at sta.uwi.edu
Md Azlin Md SaidUniversiti Sains MalaysiaVerified email at usm.my
Damith MohottiSenior Lecturer at UNSW Canberra, Honorary Associate Professor at UOWVerified email at unsw.edu.au
Sajani GamageSri Lanka Institute of Information TechnologyVerified email at sliit.lk
Sandini PalithaSri Lanka Institute of Information Technology –SLIITVerified email at sliit.lk
Kasun WijesooriyaThe University of New South Wales, CanberraVerified email at unsw.edu.au
Nitin MuttilSenior Lecturer of Water Resources, Victoria University, MelbourneVerified email at vu.edu.au
Sumudu HerathUniversity of MoratuwaVerified email at uom.lk
Dr. R. GobirahavanSenior Lecturer, Department of Civil and Environmental Engineering, Faculty of EngineeringVerified email at cee.ruh.ac.lk
Rochana RanasingheVerified email at my.sliit.lk
W.K.V.J.B. KulasooriyaBSc.Eng, Civil EngineeringVerified email at my.sliit.lk

Imesh Udara Ekanayake

Other namesI.U. Ekanayake, Imesh Ekanayake

Computer Engineer / Phd Candidate at RMIT

Verified email at eng.pdn.ac.lk - Homepage

Applied Machine Learning AI Fairness AI Privacy Explainable AI


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A novel approach to explain the black-box nature of machine learning in compressive strength predictions of concrete using Shapley additive explanations (SHAP) IU Ekanayake, DPP Meddage, U Rathnayake Case Studies in Construction Materials, e01059, 2022	120	2022
Chronic kidney disease prediction using machine learning methods IU Ekanayake, D Herath 2020 Moratuwa Engineering Research Conference (MERCon), 260-265, 2020	64	2020
Explainable Machine Learning (XML) to predict external wind pressure of a low-rise building in urban-like settings DPP Meddage, IU Ekanayake, AU Weerasuriya, CS Lewangamage, ... Journal of Wind Engineering and Industrial Aerodynamics 226, 105027, 2022	29	2022
Interpretation of machine-learning-based (black-box) wind pressure predictions for low-rise gable-roofed buildings using Shapley additive explanations (SHAP) P Meddage, I Ekanayake, US Perera, HM Azamathulla, MA Md Said, ... Buildings 12 (6), 734, 2022	24	2022
Predicting adhesion strength of micropatterned surfaces using gradient boosting models and explainable artificial intelligence visualizations IU Ekanayake, S Palitha, S Gamage, DPP Meddage, K Wijesooriya, ... Materials Today Communications 36, 106545, 2023	18	2023
Tree-based Regression Models for Predicting External Wind Pressure of a Building with an Unconventional Configuration DPP Meddage, IU Ekanayake, CS Lewangamage, AU Weerasuriya 2021 Moratuwa Engineering Research Conference (MERCon), 2021	18	2021
Predicting bulk average velocity with rigid vegetation in open channels using tree-based machine learning: a novel approach using explainable artificial intelligence DPP Meddage, IU Ekanayake, S Herath, R Gobirahavan, N Muttil, ... Sensors 22 (12), 4398, 2022	16	2022
Modeling strength characteristics of basalt fiber reinforced concrete using multiple explainable machine learning with a graphical user interface W Kulasooriya, RSS Ranasinghe, US Perera, P Thisovithan, ... Scientific Reports 13 (1), 13138, 2023	14	2023
A novel explainable AI-based approach to estimate the natural period of vibration of masonry infill reinforced concrete frame structures using different machine learning techniques P Thisovithan, H Aththanayake, DPP Meddage, IU Ekanayake, ... Results in Engineering 19, 101388, 2023	13	2023
A novel approach to explain the black-box nature of machine learning in compressive strength predictions of concrete using Shapley additive explanations (SHAP), Case Stud … IU Ekanayake, DPP Meddage, U Rathnayake	8
Modeling streamflow in non-gauged watersheds with sparse data considering physiographic, dynamic climate, and anthropogenic factors using explainable soft computing techniques C Madhushani, K Dananjaya, IU Ekanayake, DPP Meddage, ... Journal of Hydrology, 130846, 2024	5	2024
A new frontier in streamflow modeling in ungauged basins with sparse data: A modified generative adversarial network with explainable AI U Perera, DTS Coralage, IU Ekanayake, J Alawatugoda, DPP Meddage Results in Engineering, 101920, 2024	2	2024
Case Studies in Construction Materials IU Ekanayake, DPP Meddage, U Rathnayake	1	2022
Segmentation and significance of herniation measurement using Lumbar Intervertebral Discs from the Axial View Y Siriwardhana, D Karunarathna, IU Ekanayake		2022
Results in Engineering U Perera, DTS Coralage, IU Ekanayake, J Alawatugoda, DPP Meddage
Results in Engineering P Thisovithan, H Aththanayake, DPP Meddage, IU Ekanayake, ...

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