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Editorial : Statistical Learning for Predicting Air Quality
Rybarczyk, Yves Philippe
Dalarna University, School of Information and Engineering, Microdata Analysis.
ORCID iD:
0000-0002-3650-9162
Zalakeviciute, Rasa
Universidad de Las Américas, Quito, Ecuador.
2022 (English)
In:
Frontiers in big data, ISSN 2624-909X, Vol. 5, article id 898643
Article in journal, Editorial material (Other academic) Published
Place, publisher, year, edition, pages
2022. Vol. 5, article id 898643
Keywords [en]
chemical transport model (CTM), deep learning, forecast, machine learning, urban pollution
National Category
Computer and Information Sciences Earth and Related Environmental Sciences
Identifiers
URN:
urn:nbn:se:du-41518
DOI:
10.3389/fdata.2022.898643
ISI:
000798107400001
PubMedID:
35600328
Scopus ID:
2-s2.0-85130624444
OAI: oai:DiVA.org:du-41518
DiVA, id:
diva2:1662185
Available from:
2022-05-31
Created:
2022-05-31
Last updated:
2025-01-31
Bibliographically approved
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(94 kB)
123 downloads
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9d07e2085743f841c5d361671507b1a8d0bc38ae4b02f4f032e00858f6d4968a1e829e49b8f875f4c244e83db06897718ced0d18e410a23e85df1b60d03887a2
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Rybarczyk, Yves Philippe
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Permanent link
https://urn.kb.se/resolve?urn=urn:nbn:se:du-41518
Direct link
http://du.diva-portal.org/smash/record.jsf?pid=diva2:1662185
Cite
Citation style
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ieee
modern-language-association-8th-edition
vancouver
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apa
ieee
modern-language-association-8th-edition
vancouver
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Other style
More styles
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de-DE
en-GB
en-US
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nn-NO
nn-NB
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en-GB
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text
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text
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