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D.P.P. Meddage
Observed names:
D. P. P. Meddage,
Don Pasindu Piumal Meddage,
Meddage, Pasindu,
Pasindu Meddage
Institutions:
Sri Lanka Institute of Information Technology,
UNSW Sydney,
UNSW Canberra
Observed institutions:
University of Peradeniya,
University of Ruhuna,
Sri Lanka Institute of Information Technology,
University of Moratuwa,
UNSW Sydney,
UNSW Canberra
show all 6
ORCID:
0000-0002-9938-5267
Observed ORCID:
0000-0002-9938-5267
OpenAlex ID:
A5034038081
A novel approach to explain the black-box nature of machine learning in compressive strength predictions of concrete using Shapley additive explanations (SHAP)
2022
·
I.U. Ekanayake
, D.P.P. Meddage
, et al.
·
Case Studies in Construction Materials
·
550
PDF
Adapting cities to the surge: A comprehensive review of climate-induced urban flooding
2024
·
Gangani Dharmarathne
, A.O. Waduge
, et al.
·
Results in Engineering
·
283
Advancing water quality assessment and prediction using machine learning models, coupled with explainable artificial intelligence (XAI) techniques like shapley additive explanations (SHAP) for interpreting the black-box nature
2024
·
Randika K. Makumbura
, Lakindu Mampitiya
, et al.
·
Results in Engineering
·
264
A review of machine learning (ML) and explainable artificial intelligence (XAI) methods in additive manufacturing (3D Printing)
2024
·
Jeewanthi Ukwaththa
, Sumudu Herath
, et al.
·
Materials Today Communications
·
135
A novel machine learning approach for diagnosing diabetes with a self-explainable interface
2024
·
Gangani Dharmarathne
, Thilini N. Jayasinghe
, et al.
·
Healthcare Analytics
·
126
A review of machine learning and internet-of-things on the water quality assessment: Methods, applications and future trends
2025
·
Gangani Dharmarathne
, A.M.S.R. Abekoon
, et al.
·
Results in Engineering
·
104
Explainable Machine Learning (XML) to predict external wind pressure of a low-rise building in urban-like settings
2022
·
D.P.P. Meddage
, I.U. Ekanayake
, et al.
·
Journal of Wind Engineering and Industrial Aerodynamics
·
103
Evaluating expressway traffic crash severity by using logistic regression and explainable & supervised machine learning classifiers
2023
·
J.P.S. Shashiprabha Madushani
, R.M. Kelum Sandamal
, et al.
·
Transportation Engineering
·
92
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
2023
·
P. Thisovithan
, Harinda Aththanayake
, et al.
·
Results in Engineering
·
89
An explainable machine learning approach to predict the compressive strength of graphene oxide-based concrete
2024
·
D.P.P. Meddage
, Isuri Fonseka
, et al.
·
Construction and Building Materials
·
81
Modeling streamflow in non-gauged watersheds with sparse data considering physiographic, dynamic climate, and anthropogenic factors using explainable soft computing techniques
2024
·
Charuni Madhushani
, Kusal Dananjaya
, et al.
·
Journal of Hydrology
·
75
Modeling strength characteristics of basalt fiber reinforced concrete using multiple explainable machine learning with a graphical user interface
2023
·
W. K. V. J. B. Kulasooriya
, R. S. S. Ranasinghe
, et al.
·
Scientific Reports
·
75
PDF
On the diagnosis of chronic kidney disease using a machine learning-based interface with explainable artificial intelligence
2024
·
Gangani Dharmarathne
, Madhusha Bogahawaththa
, et al.
·
Intelligent Systems with Applications
·
69
Interpretation of Machine-Learning-Based (Black-box) Wind Pressure Predictions for Low-Rise Gable-Roofed Buildings Using Shapley Additive Explanations (SHAP)
2022
·
Pasindu Meddage
, Imesh Ekanayake
, et al.
·
Buildings
·
61
PDF
Eco-friendly mix design of slag-ash-based geopolymer concrete using explainable deep learning
2024
·
R.S.S. Ranasinghe
, W.K.V.J.B. Kulasooriya
, et al.
·
Results in Engineering
·
57
Predicting transient wind loads on tall buildings in three-dimensional spatial coordinates using machine learning
2024
·
D.P.P. Meddage
, Damith Mohotti
, et al.
·
Journal of Building Engineering
·
53
A Simplified Mathematical Formulation for Water Quality Index (WQI): A Case Study in the Kelani River Basin, Sri Lanka
2022
·
Randika Makubura
, D. P. P. Meddage
, et al.
·
Fluids
·
45
PDF
Exploring the applicability of expanded polystyrene (EPS) based concrete panels as roof slab insulation in the tropics
2022
·
D.P.P. Meddage
, Aaron Chadee
, et al.
·
Case Studies in Construction Materials
·
44
PDF
In-depth simulation of rainfall–runoff relationships using machine learning methods
2024
·
Mehdi Fuladipanah
, Alireza Shahhosseini
, et al.
·
Water Practice & Technology
·
43
A new frontier in streamflow modeling in ungauged basins with sparse data: A modified generative adversarial network with explainable AI
2024
·
U.A.K.K. Perera
, D.T.S. Coralage
, et al.
·
Results in Engineering
·
41
Predicting adhesion strength of micropatterned surfaces using gradient boosting models and explainable artificial intelligence visualizations
2023
·
I.U. Ekanayake
, Sandini Palitha
, et al.
·
Materials Today Communications
·
38
Use of explainable machine learning models in blast load prediction
2024
·
C. Widanage
, D. Mohotti
, et al.
·
Engineering Structures
·
36
Predicting Bulk Average Velocity with Rigid Vegetation in Open Channels Using Tree-Based Machine Learning: A Novel Approach Using Explainable Artificial Intelligence
2022
·
D. P. P. Meddage
, I. U. Ekanayake
, et al.
·
Sensors
·
34
PDF
Machine learning approach to predict the mechanical properties of cementitious materials containing carbon nanotubes
2024
·
Nader M. Okasha
, Masoomeh Mirrashid
, et al.
·
Developments in the Built Environment
·
33
Tree-based Regression Models for Predicting External Wind Pressure of a Building with an Unconventional Configuration
2021
·
D. P. P. Meddage
, Imesh Udara Ekanayake
, et al.
·
Moratuwa Engineering Research Conference (MERCon)
·
27
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Works count:
52
Citation count:
2,750
H-index:
25
I10-index:
32
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