Zobrazeno 1 - 10
of 48
pro vyhledávání: '"D.P.P. Meddage"'
Autor:
Nader M. Okasha, Masoomeh Mirrashid, Hosein Naderpour, Aybike Ozyuksel Ciftcioglu, D.P.P. Meddage, Nima Ezami
Publikováno v:
Developments in the Built Environment, Vol 19, Iss , Pp 100494- (2024)
This research explores the use of machine learning to predict the mechanical properties of cementitious materials enhanced with carbon nanotubes (CNTs). Specifically, the study focuses on estimating the elastic modulus and flexural strength of these
Externí odkaz:
https://doaj.org/article/8cdd725694a94895bb2a8a17929464b7
Publikováno v:
Intelligent Systems with Applications, Vol 23, Iss , Pp 200428- (2024)
Conventional machine learning techniques in diagnosing cardiovascular disease have a limitation owing to the lack of interpretability of models. This study utilised an explainable machine learning approach to predict the likelihood of having CVD. Fou
Externí odkaz:
https://doaj.org/article/5659dd1738c94fecb4ad3f40fa08a96f
Autor:
Randika K. Makumbura, Lakindu Mampitiya, Namal Rathnayake, D.P.P. Meddage, Shagufta Henna, Tuan Linh Dang, Yukinobu Hoshino, Upaka Rathnayake
Publikováno v:
Results in Engineering, Vol 23, Iss , Pp 102831- (2024)
Water quality assessment and prediction play crucial roles in ensuring the sustainability and safety of freshwater resources. This study aims to enhance water quality assessment and prediction by integrating advanced machine learning models with XAI
Externí odkaz:
https://doaj.org/article/8e53500fbc9e4d9db24eacbbdc03b624
Autor:
R.S.S. Ranasinghe, W.K.V.J.B. Kulasooriya, Udara Sachinthana Perera, I.U. Ekanayake, D.P.P. Meddage, Damith Mohotti, Upaka Rathanayake
Publikováno v:
Results in Engineering, Vol 23, Iss , Pp 102503- (2024)
Geopolymer concrete is a sustainable and eco-friendly substitute for traditional OPC (Ordinary Portland Cement) based concrete, as it reduces greenhouse gas emissions. With various supplementary cementitious materials, the compressive strength of geo
Externí odkaz:
https://doaj.org/article/a23fb37a78af41bab65c1a604ae88e73
Autor:
N.D. Wimalagunarathna, Gangani Dharmarathne, I.U. Ekanayake, Upaka Rathanayake, Janaka Alwatugoda, D.P.P. Meddage
Publikováno v:
Case Studies in Chemical and Environmental Engineering, Vol 10, Iss , Pp 100919- (2024)
Freshwater salinisation and alkalinisation strongly depend on human and natural factors. We used an explainable machine learning approach to investigate the impact of natural and human factors on the salinity and alkalinity in rivers in the United St
Externí odkaz:
https://doaj.org/article/103dc5dcf9214de4a5ac086fe2261538
Publikováno v:
Results in Engineering, Vol 22, Iss , Pp 102123- (2024)
Climate change is a serious global issue causing more extreme weather patterns, resulting in more frequent and severe events like urban flooding. This review explores the connection between climate change and urban flooding, offering statistical, sci
Externí odkaz:
https://doaj.org/article/a2730f0e52014e1b92b339c5d4918368
Autor:
Gangani Dharmarathne, Madhusha Bogahawaththa, Marion McAfee, Upaka Rathnayake, D.P.P. Meddage
Publikováno v:
Intelligent Systems with Applications, Vol 22, Iss , Pp 200397- (2024)
Chronic Kidney Disease (CKD) is increasingly recognised as a major health concern due to its rising prevalence. The average survival period without functioning kidneys is typically limited to approximately 18 days, creating a significant need for kid
Externí odkaz:
https://doaj.org/article/67c9ed4ae3674ade891af612ab03c713
Autor:
Thilina Abekoon, Hirushan Sajindra, B.L.S.K. Buthpitiya, Namal Rathnayake, D.P.P. Meddage, Upaka Rathnayake
Publikováno v:
MethodsX, Vol 12, Iss , Pp 102793- (2024)
In a recent paper by Sajindra et al. [1], the soil nutrient levels, specifically nitrogen, phosphorus, and potassium, in organic cabbage cultivation were predicted using a deep learning model. This model was designed with a total of four hidden layer
Externí odkaz:
https://doaj.org/article/d1412d3be4184f208282ef9f4ca32fba
Autor:
Gangani Dharmarathne, Thilini N. Jayasinghe, Madhusha Bogahawaththa, D.P.P. Meddage, Upaka Rathnayake
Publikováno v:
Healthcare Analytics, Vol 5, Iss , Pp 100301- (2024)
This study introduces the first-ever self-explanatory interface for diagnosing diabetes patients using machine learning. We propose four classification models (Decision Tree (DT), K-nearest Neighbor (KNN), Support Vector Classification (SVC), and Ext
Externí odkaz:
https://doaj.org/article/065e628a15c94b4896634217032c474b
Publikováno v:
Results in Engineering, Vol 21, Iss , Pp 101920- (2024)
Streamflow forecasting is crucial for effective water resource planning and early warning systems, especially in regions with complex hydrological behaviors and uncertainties. While machine learning (ML) has gained popularity for streamflow predictio
Externí odkaz:
https://doaj.org/article/64ccd233fc354cdbb285a231cf3a5931