Artificial neural networks can be used for Ambrosia pollen emission parameterization in COSMO-ART Article Swipe
Charlotte Bürki
,
Branko Šikoparija
,
M. Thibaudon
,
G. Oliver
,
Donát Magyar
,
Orsolya Udvardy
,
Ádám Leelőssy
,
Christophe Charpilloz
,
Andreas Pauling
·
YOU?
·
· 2019
· Open Access
·
· DOI: https://doi.org/10.1016/j.atmosenv.2019.116969
YOU?
·
· 2019
· Open Access
·
· DOI: https://doi.org/10.1016/j.atmosenv.2019.116969
Related Topics
Concepts
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1016/j.atmosenv.2019.116969
- OA Status
- green
- Cited By
- 8
- References
- 38
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W2972947291
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W2972947291Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1016/j.atmosenv.2019.116969Digital Object Identifier
- Title
-
Artificial neural networks can be used for Ambrosia pollen emission parameterization in COSMO-ARTWork title
- Type
-
articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2019Year of publication
- Publication date
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2019-09-13Full publication date if available
- Authors
-
Charlotte Bürki, Branko Šikoparija, M. Thibaudon, G. Oliver, Donát Magyar, Orsolya Udvardy, Ádám Leelőssy, Christophe Charpilloz, Andreas PaulingList of authors in order
- Landing page
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https://doi.org/10.1016/j.atmosenv.2019.116969Publisher landing page
- Open access
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YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
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https://infoscience.epfl.ch/record/273410Direct OA link when available
- Concepts
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Pollen, Artificial neural network, Sigmoid function, Dispersion (optics), Benchmark (surveying), Variable (mathematics), Environmental science, Ambrosia, Meteorology, Mathematics, Computer science, Machine learning, Geography, Physics, Botany, Cartography, Optics, Biology, Mathematical analysisTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
8Total citation count in OpenAlex
- Citations by year (recent)
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2024: 2, 2021: 1, 2020: 3, 2019: 1Per-year citation counts (last 5 years)
- References (count)
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38Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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