Zobrazeno 1 - 5
of 5
pro vyhledávání: '"L. H. Leufen"'
Publikováno v:
Geoscientific Model Development, Vol 15, Pp 8913-8930 (2022)
Tropospheric ozone is a secondary air pollutant that is harmful to living beings and crops. Predicting ozone concentrations at specific locations is thus important to initiate protection measures, i.e. emission reductions or warnings to the populatio
Externí odkaz:
https://doaj.org/article/c6005c09a18a400b9f6b739d518da0db
Publikováno v:
Geoscientific Model Development, Vol 14, Pp 1553-1574 (2021)
With MLAir (Machine Learning on Air data) we created a software environment that simplifies and accelerates the exploration of new machine learning (ML) models, specifically shallow and deep neural networks, for the analysis and forecasting of meteor
Externí odkaz:
https://doaj.org/article/f84e6b7a390349a29377b046115b2292
IntelliO3-ts v1.0: a neural network approach to predict near-surface ozone concentrations in Germany
Publikováno v:
Geoscientific Model Development, Vol 14, Pp 1-25 (2021)
The prediction of near-surface ozone concentrations is important for supporting regulatory procedures for the protection of humans from high exposure to air pollution. In this study, we introduce a data-driven forecasting model named “IntelliO3-ts
Externí odkaz:
https://doaj.org/article/833bceaea8494179a77bd558bbce9559
Autor:
L. H. Leufen, G. Schädler
Publikováno v:
Geoscientific Model Development, Vol 12, Pp 2033-2047 (2019)
The turbulent fluxes of momentum, heat and water vapour link the Earth's surface with the atmosphere. Therefore, the correct modelling of the flux interactions between these two systems with very different timescales is vital for climate and weather
Externí odkaz:
https://doaj.org/article/6fa26c3a2730460cab8f0228679634e0
Autor:
M G, Schultz, C, Betancourt, B, Gong, F, Kleinert, M, Langguth, L H, Leufen, A, Mozaffari, S, Stadtler
Publikováno v:
Philosophical transactions of the Royal Society of London / A 379(2194), 20200097 (2021). doi:10.1098/rsta.2020.0097 special issue: "Machine learning for weather and climate modelling"
Philosophical transactions. Series A, Mathematical, physical, and engineering sciences
Philosophical transactions. Series A, Mathematical, physical, and engineering sciences
The recent hype about artificial intelligence has sparked renewed interest in applying the successful deep learning (DL) methods for image recognition, speech recognition, robotics, strategic games and other application areas to the field of meteorol
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=pmid_dedup__::ae8f05a1d8fcb7e02f258aa752d317ff
https://hdl.handle.net/2128/27491
https://hdl.handle.net/2128/27491