Zobrazeno 1 - 10
of 56
pro vyhledávání: '"Jeevani Jayasinghe"'
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:
AIMS Electronics and Electrical Engineering, Vol 6, Iss 1, Pp 1-15 (2022)
Multi-band microstrip patch antennas are convenient for mm-wave wireless applications due to their low profile, less weight, and planar structure. This paper investigates patch geometry optimization of a single microstrip antenna by employing a binar
Externí odkaz:
https://doaj.org/article/4134e0e3a8a04623a85ac75fc9b778d0
Publikováno v:
EAI Endorsed Transactions on Mobile Communications and Applications, Vol 7, Iss 21 (2022)
The demand for high data rates, combined with the exponential growth of mobile data trafficking, and has prompted the use of millimeter-wave (mm-wave) spectrum for 5G mobile communication. So, for constructive assessment, this study employed various
Externí odkaz:
https://doaj.org/article/a6c38a1214e641b0bfdf329d37c14a81
Publikováno v:
International Journal of Antennas and Propagation, Vol 2022 (2022)
This paper presents the design of a novel fabric-based multi-band microstrip antenna in mm-wave frequencies for wearable applications. The reference patch antenna was etched on a flexible polytetrafluoroethylene (PTFE) fabric substrate with an overal
Externí odkaz:
https://doaj.org/article/a228f1bc2733480ab3ceae55cd4f2b08
Publikováno v:
Applied Computational Intelligence and Soft Computing, Vol 2022 (2022)
This paper presents the development of a wind power forecasting model based on gene expression programming (GEP) for one of the major wind farms in Sri Lanka, Pawan Danavi. With the ever-increasing demand for renewable power generation, Sri Lanka has
Externí odkaz:
https://doaj.org/article/56fb945af6c1444b8710bca72f1099de
Publikováno v:
Technologies, Vol 11, Iss 1, p 14 (2023)
Antennas with multifunctional capabilities integrated into a single device that demonstrates a high performance are in demand, and microstrip antennas with quadband coverage are very useful for a wide range of mm-wave applications. Antennas and propa
Externí odkaz:
https://doaj.org/article/b0ceec3370214d4db87fc0bdaba6581a
Publikováno v:
Journal of Electrical and Computer Engineering, Vol 2021 (2021)
Wind power, as a renewable energy resource, has taken much attention of the energy authorities in many countries, as it is used as one of the major energy sources to satisfy the ever-increasing energy demand. However, careful attention is needed in i
Externí odkaz:
https://doaj.org/article/984c12f811334dff8c1e2ef4f457fde5
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
Autor:
Jaume Anguera, Aurora Andújar, Jeevani Jayasinghe, V. V. S. S. Sameer Chakravarthy, P. S. R. Chowdary, Joan L. Pijoan, Tanweer Ali, Carlo Cattani
Publikováno v:
Fractal and Fractional, Vol 4, Iss 1, p 3 (2020)
Fractal geometry has been proven to be useful in several disciplines. In the field of antenna engineering, fractal geometry is useful to design small and multiband antenna and arrays, and high-directive elements. A historic overview of the most signi
Externí odkaz:
https://doaj.org/article/134bed5d722f47848d2c7ac09e5cecba
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