Hasil Pencarian - D.P.P. Meddage

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  1. 1
    A novel approach to explain the black-box nature of machine learning in compressive strength predictions of concrete using Shapley additive explanations (SHAP)

    A novel approach to explain the black-box nature of machine learning in compressive strength predictions of concrete using Shapley additive explanations (SHAP) oleh I.U. Ekanayake, D.P.P. Meddage, Upaka Rathnayake

    Diterbitkan 2022-06-01
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  2. 2
    Integrating explainable machine learning and user-centric model for diagnosing cardiovascular disease: A novel approach

    Integrating explainable machine learning and user-centric model for diagnosing cardiovascular disease: A novel approach oleh Gangani Dharmarathne, Madhusha Bogahawaththa, Upaka Rathnayake, D.P.P. Meddage

    Diterbitkan 2024-09-01
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  3. 3
    Exploring the applicability of expanded polystyrene (EPS) based concrete panels as roof slab insulation in the tropics

    Exploring the applicability of expanded polystyrene (EPS) based concrete panels as roof slab insulation in the tropics oleh D.P.P. Meddage, Aaron Chadee, M.T.R. Jayasinghe, Upaka Rathnayake

    Diterbitkan 2022-12-01
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  4. 4
    A novel machine learning approach for diagnosing diabetes with a self-explainable interface

    A novel machine learning approach for diagnosing diabetes with a self-explainable interface oleh Gangani Dharmarathne, Thilini N. Jayasinghe, Madhusha Bogahawaththa, D.P.P. Meddage, Upaka Rathnayake

    Diterbitkan 2024-06-01
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  5. 5
    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

    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 oleh P. Thisovithan, Harinda Aththanayake, D.P.P. Meddage, I.U. Ekanayake, Upaka Rathnayake

    Diterbitkan 2023-09-01
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  6. 6
    On the diagnosis of chronic kidney disease using a machine learning-based interface with explainable artificial intelligence

    On the diagnosis of chronic kidney disease using a machine learning-based interface with explainable artificial intelligence oleh Gangani Dharmarathne, Madhusha Bogahawaththa, Marion McAfee, Upaka Rathnayake, D.P.P. Meddage

    Diterbitkan 2024-06-01
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  7. 7
    A Simplified Mathematical Formulation for Water Quality Index (WQI): A Case Study in the Kelani River Basin, Sri Lanka

    A Simplified Mathematical Formulation for Water Quality Index (WQI): A Case Study in the Kelani River Basin, Sri Lanka oleh Randika Makubura, D. P. P. Meddage, Hazi Md. Azamathulla, Manish Pandey, Upaka Rathnayake

    Diterbitkan 2022-04-01
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  8. 8
    Adapting cities to the surge: A comprehensive review of climate-induced urban flooding

    Adapting cities to the surge: A comprehensive review of climate-induced urban flooding oleh Gangani Dharmarathne, A.O. Waduge, Madhusha Bogahawaththa, Upaka Rathnayake, D.P.P. Meddage

    Diterbitkan 2024-06-01
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  9. 9
    Influence of Crumb Rubber and Coconut Coir on Strength and Durability Characteristics of Interlocking Paving Blocks

    Influence of Crumb Rubber and Coconut Coir on Strength and Durability Characteristics of Interlocking Paving Blocks oleh Sajani Gamage, Sandini Palitha, D. P. P. Meddage, Shayani Mendis, Hazi Md. Azamathulla, Upaka Rathnayake

    Diterbitkan 2022-07-01
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  10. 10
    Predicting Bulk Average Velocity with Rigid Vegetation in Open Channels Using Tree-Based Machine Learning: A Novel Approach Using Explainable Artificial Intelligence

    Predicting Bulk Average Velocity with Rigid Vegetation in Open Channels Using Tree-Based Machine Learning: A Novel Approach Using Explainable Artificial Intelligence oleh D. P. P. Meddage, I. U. Ekanayake, Sumudu Herath, R. Gobirahavan, Nitin Muttil, Upaka Rathnayake

    Diterbitkan 2022-06-01
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  11. 11
    Effect of endogenous and anthropogenic factors on the alkalinisation and salinisation of freshwater in United States by using explainable machine learning

    Effect of endogenous and anthropogenic factors on the alkalinisation and salinisation of freshwater in United States by using explainable machine learning oleh N.D. Wimalagunarathna, Gangani Dharmarathne, I.U. Ekanayake, Upaka Rathanayake, Janaka Alwatugoda, D.P.P. Meddage

    Diterbitkan 2024-12-01
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  12. 12
    A new frontier in streamflow modeling in ungauged basins with sparse data: A modified generative adversarial network with explainable AI

    A new frontier in streamflow modeling in ungauged basins with sparse data: A modified generative adversarial network with explainable AI oleh U.A.K.K. Perera, D.T.S. Coralage, I.U. Ekanayake, Janaka Alawatugoda, D.P.P. Meddage

    Diterbitkan 2024-03-01
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  13. 13
    Machine learning approach to predict the mechanical properties of cementitious materials containing carbon nanotubes

    Machine learning approach to predict the mechanical properties of cementitious materials containing carbon nanotubes oleh Nader M. Okasha, Masoomeh Mirrashid, Hosein Naderpour, Aybike Ozyuksel Ciftcioglu, D.P.P. Meddage, Nima Ezami

    Diterbitkan 2024-10-01
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  14. 14
    Justifying the prediction of major soil nutrients levels (N, P, and K) in cabbage cultivation

    Justifying the prediction of major soil nutrients levels (N, P, and K) in cabbage cultivation oleh Thilina Abekoon, Hirushan Sajindra, B.L.S.K. Buthpitiya, Namal Rathnayake, D.P.P. Meddage, Upaka Rathnayake

    Diterbitkan 2024-06-01
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  15. 15
    In-depth simulation of rainfall–runoff relationships using machine learning methods

    In-depth simulation of rainfall–runoff relationships using machine learning methods oleh Mehdi Fuladipanah, Alireza Shahhosseini, Namal Rathnayake, Hazi Md. Azamathulla, Upaka Rathnayake, D. P. P. Meddage, Kiran Tota-Maharaj

    Diterbitkan 2024-06-01
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  16. 16
    Evaluating expressway traffic crash severity by using logistic regression and explainable & supervised machine learning classifiers

    Evaluating expressway traffic crash severity by using logistic regression and explainable & supervised machine learning classifiers oleh J.P.S. Shashiprabha Madushani, R.M. Kelum Sandamal, D.P.P. Meddage, H.R. Pasindu, P.I. Ayantha Gomes

    Diterbitkan 2023-09-01
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  17. 17
    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

    Advancing water quality assessment and prediction using machine learning models, coupled with explainable artificial intelligence (XAI) techniques like shapley additive explanation... oleh Randika K. Makumbura, Lakindu Mampitiya, Namal Rathnayake, D.P.P. Meddage, Shagufta Henna, Tuan Linh Dang, Yukinobu Hoshino, Upaka Rathnayake

    Diterbitkan 2024-09-01
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  18. 18
    Modeling strength characteristics of basalt fiber reinforced concrete using multiple explainable machine learning with a graphical user interface

    Modeling strength characteristics of basalt fiber reinforced concrete using multiple explainable machine learning with a graphical user interface oleh W. K. V. J. B. Kulasooriya, R. S. S. Ranasinghe, Udara Sachinthana Perera, P. Thisovithan, I. U. Ekanayake, D. P. P. Meddage

    Diterbitkan 2023-08-01
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  19. 19
    Eco-friendly mix design of slag-ash-based geopolymer concrete using explainable deep learning

    Eco-friendly mix design of slag-ash-based geopolymer concrete using explainable deep learning oleh R.S.S. Ranasinghe, W.K.V.J.B. Kulasooriya, Udara Sachinthana Perera, I.U. Ekanayake, D.P.P. Meddage, Damith Mohotti, Upaka Rathanayake

    Diterbitkan 2024-09-01
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