Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Piyal Ekanayake"'
Autor:
Jeevani Jayasinghe, Piyal Ekanayake, Oshadi Panahatipola, Charuni I. Madhushani, Upaka Rathnayake
Publikováno v:
Results in Engineering, Vol 22, Iss , Pp 102111- (2024)
This paper presents the application of regression trees as a versatile alternative to other machine learning and statistical modelling techniques to forecast the power generation at five renewable power plants: one large hydropower plant, two mini hy
Externí odkaz:
https://doaj.org/article/274338035daa4d308b3f3239438c9632
Publikováno v:
Journal of Mathematics, Vol 2021 (2021)
This paper presents the application of a multiple number of statistical methods and machine learning techniques to model the relationship between rice yield and climate variables of a major region in Sri Lanka, which contributes significantly to the
Externí odkaz:
https://doaj.org/article/135d5c6e33ac4c9eb1d9965471f414ac
Publikováno v:
Journal of Mathematics, Vol 2021 (2021)
This paper presents the development of crop-weather models for the paddy yield in Sri Lanka based on nine weather indices, namely, rainfall, relative humidity (minimum and maximum), temperature (minimum and maximum), wind speed (morning and evening),
Externí odkaz:
https://doaj.org/article/71029559f4b945ceb4d1aa4964bd9cb3
Publikováno v:
Volume: 35, Issue: 4 1359-1370
Gazi University Journal of Science
Gazi University Journal of Science
This paper presents the development of wind energy prediction models for the Nala Danavi wind farm in Sri Lanka by using machine learning and statistical techniques. Wind speed and ambient temperature were used as the input variables in modeling whil
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d69ad9431b3d164e9b893365dae95e69
https://doi.org/10.35378/gujs.961338
https://doi.org/10.35378/gujs.961338
Publikováno v:
Mathematical Problems in Engineering, Vol 2021 (2021)
This paper presents the development of models for the prediction of power generation at the Samanalawewa hydropower plant, which is one of the major power stations in Sri Lanka. Four regression-based machine learning and statistical techniques were a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::eb90d76581e3831108640ecd9c496d84
https://doi.org/10.1155/2021/4913824
https://doi.org/10.1155/2021/4913824
Publikováno v:
Mathematical Problems in Engineering, Vol 2021 (2021)
This paper presents the development of wind power prediction models for a wind farm in Sri Lanka using an artificial neural network (ANN), multiple linear regression (MLR), and power regression (PR) techniques. Power generation data over five years s
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::65d2cb4978c9fef13909395c3a7fdc45
https://doaj.org/article/4d9fcb24e7964e90b75bb029a6547a70
https://doaj.org/article/4d9fcb24e7964e90b75bb029a6547a70
Publikováno v:
Journal of Mathematics, Vol 2021 (2021)
This paper presents the application of a multiple number of statistical methods and machine learning techniques to model the relationship between rice yield and climate variables of a major region in Sri Lanka, which contributes significantly to the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::bbf6638a76e18aa4793a64e01f12649d
