Representing chemical history in ozone time-series predictions – a model experiment study building on the MLAir (v1.5) deep learning framework

Autor: F. Kleinert, L. H. Leufen, A. Lupascu, T. Butler, M. G. Schultz

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

IntelliO3-ts v1.0: a neural network approach to predict near-surface ozone concentrations in Germany

Autor: F. Kleinert, L. H. Leufen, M. G. Schultz

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

Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.

Can deep learning beat numerical weather prediction?

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

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

Die lebenszyklusorientierte Wertstromanalyse*/Life cycle-oriented value stream mapping – Comprehensively identifying digitization options in the life cycle of cutting tools

Autor: F. Kleinert, E. Westkämper, F. Schröter, D. Brenner

Publikováno v: wt Werkstattstechnik online. 108:821-828

Aus der fortschreitenden Entwicklung informationstechnischer Kommunikation zur Vernetzung aller Prozesse im Werkzeuglebenszyklus und der Technologie zur Prozessbeobachtung ergeben sich neue Potenziale zur Systemeffizienzsteigerung des Werkzeugwesens.

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::6e0ab1018170eccfdf41c5b0f1892868
https://doi.org/10.37544/1436-4980-2018-11-12-81