Zobrazeno 1 - 10
of 4 455
pro vyhledávání: '"Weather data"'
Autor:
Aminda Amarasinghe, Ishini Sangarasekara, Nuwan De Silva, Mojith Ariyaratne, Ruwanga Amarasinghe, Jinendra Bogahawatte, Janaka Alawatugoda, Damayanthi Herath
Publikováno v:
Discover Applied Sciences, Vol 6, Iss 11, Pp 1-26 (2024)
Abstract Food sustainability is crucial aspect in achieving several United Nations (UN) Sustainable Development Goals (SDGs). By integrating advanced technologies for reliable and accurate decision-making, we can advance food sustainability and, cons
Externí odkaz:
https://doaj.org/article/88a3541ef2fc44c3bce171fcb8a41535
Publikováno v:
Applied Water Science, Vol 14, Iss 9, Pp 1-21 (2024)
Abstract Accurate estimation of ET is vital for water resource management. In recent decades, researchers have focused on utilizing satellite imagery for this purpose. The use of RS data has enabled the development of new models that provide detailed
Externí odkaz:
https://doaj.org/article/bae338caddb944d0b36aa1b4dfe1b996
Publikováno v:
Fuels, Vol 5, Iss 3, Pp 278-296 (2024)
This paper aims to study the performance of solar collectors of various sizes under different weather conditions in different Japanese cities, i.e., Kofu City, Nagoya City and Yamagata City. The heat generated by the solar collector was used to condu
Externí odkaz:
https://doaj.org/article/4034624f214444898b3ce3f61bcb17a5
Optimal Design and Performance Analysis of Multiple Photovoltaic with Grid-Connected Commercial Load
Publikováno v:
International Journal of Technology, Vol 15, Iss 4, Pp 834-846 (2024)
This study aimed to evaluate the potential of integrating Photovoltaic (PV) with commercial load and examine the impact on distribution networks. To estimate the hourly PV output power, 13 years of historical weather data were used. Furthermore, a
Externí odkaz:
https://doaj.org/article/72f834823b074695bab06b31b2df24a2
Autor:
Bernard Cárdenas, Michael D. Dukes
Publikováno v:
EDIS, Vol 2024, Iss 5 (2024)
The Net Irrigation Requirements for Florida Turfgrass Lawns series explains the process of estimating net irrigation requirements for Florida turfgrasses. The process used here gives a long-term (30-year) historical analysis of turfgrass monthly net
Externí odkaz:
https://doaj.org/article/7fc6f9d51ff84749880bf797e4e211aa
Autor:
Iván Gómez, Sergio Ilarri
Publikováno v:
Data in Brief, Vol 57, Iss , Pp 110878- (2024)
The proliferation of urban areas and the concurrent increase in vehicular mobility have escalated the urgency for advanced traffic management solutions. This data article introduces two traffic datasets from Madrid, collected between June 2022 and Fe
Externí odkaz:
https://doaj.org/article/b3f319b967064e6f8c62754bff27aae1
Autor:
Francisco Monteiro, Rafael Oliveira, João Almeida, Pedro Gonçalves, Paulo Bartolomeu, Jorge Neto, Ricardo Deus
Publikováno v:
Data in Brief, Vol 54, Iss , Pp 110373- (2024)
Real-world data collections are generally not easily available. Energy measurements from buildings, houses and other devices can be used within different areas of research while being employed to plan or train models, allowing the improvement of powe
Externí odkaz:
https://doaj.org/article/f93a5a3ae1a642709216bddb587d3dae
Autor:
Thiago Orlando Costa Barboza, Marcelo Araújo Junqueira Ferraz, Cristiane Pilon, George Vellidis, Taynara Tuany Borges Valeriano, Adão Felipe dos Santos
Publikováno v:
AgriEngineering, Vol 6, Iss 1, Pp 438-454 (2024)
Understanding the impact of climate on peanut growth is crucial, given the importance of temperature in peanut to accumulate Growing Degree Days (GDD). Therefore, our study aimed to compare data sourced from the NASA POWER platform with information f
Externí odkaz:
https://doaj.org/article/f4ecfa4a762e4832a7187f5d828eafbe
Autor:
Nicole Groene, Sergii Zakharov
Publikováno v:
Discover Artificial Intelligence, Vol 4, Iss 1, Pp 1-17 (2024)
Abstract Food and beverage (F&B) outlets such as restaurants, delis and fast-food joins are commonly owner-operated small businesses with limited access to modern forecasting technologies. Managers often rely on experience-based forecasting heuristic
Externí odkaz:
https://doaj.org/article/48e10c9de73c48d4a1ff50a53a5a30fc
Publikováno v:
Journal of Horticultural Research, Vol 31, Iss 2, Pp 35-44 (2023)
The study examined the performance of four machine learning algorithms (regression trees, boosted trees, random forests, and artificial neural networks) for estimating evapotranspiration (ETo) based on incomplete meteorological data. Meteorological v
Externí odkaz:
https://doaj.org/article/d9d17d8fcec2480a9f972cd224e39993