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Editorial: Statistical Learning for Predicting Air Quality

descriptionPublicationkeyboard_double_arrow_right Article , Other literature type 05 May 2022 Sweden Publisher:Frontiers Media SAJournal:Frontiers in Big Data, volume 5 (eissn: 2624-909X, Copyright policy )
Authors: Rybarczyk, Yves Philippe; Zalakeviciute, Rasa;

doi: 10.3389/fdata.2022.898643

pmid: 35600328

pmc: PMC9117751

Editorial: Statistical Learning for Predicting Air Quality

Country
Sweden
Related Organizations
Keywords

Big Data, Computer and Information Sciences, forecast, deep learning, Data- och informationsvetenskap, Information technology, T58.5-58.64, Geovetenskap och relaterad miljövetenskap, machine learning, chemical transport model (CTM), Earth and Related Environmental Sciences, urban pollution

  • BIP!
    Impact byBIP!
    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    		 2
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    		 Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    		 Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    		 Average
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
2
Average
Average
Average
Green
gold