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Editorial : Statistical Learning for Predicting Air Quality
Dalarna University, School of Information and Engineering, Microdata Analysis.ORCID iD: 0000-0002-3650-9162
Universidad de Las Américas, Quito, Ecuador.
2022 (English)In: Frontiers in Big Data, E-ISSN 2624-909X, Vol. 5, article id 898643Article 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
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URN: urn:nbn:se:du-41518DOI: 10.3389/fdata.2022.898643ISI: 000798107400001PubMedID: 35600328Scopus ID: 2-s2.0-85130624444OAI: oai:DiVA.org:du-41518DiVA, id: diva2:1662185
Available from: 2022-05-31 Created: 2022-05-31 Last updated: 2025-12-01Bibliographically approved

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fulltext(94 kB)150 downloads
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Rybarczyk, Yves Philippe

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