Predicting the ground-level pollutants concentrations and identifying the influencing factors using machine learning, wavelet transformation, and remote sensing techniques

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dc.contributor.author Taghizadeh-Mehrjardi, Ruhollah
dc.date.accessioned 2021-12-08T14:06:32Z
dc.date.available 2021-12-08T14:06:32Z
dc.date.issued 2021
dc.identifier.issn 1309-1042
dc.identifier.uri http://hdl.handle.net/10900/121628
dc.language.iso en de_DE
dc.publisher Turkish Natl Committee Air Pollution Res & Control - Tuncap de_DE
dc.relation.uri http://dx.doi.org/10.1016/j.apr.2021.101064 de_DE
dc.subject.ddc 570 de_DE
dc.title Predicting the ground-level pollutants concentrations and identifying the influencing factors using machine learning, wavelet transformation, and remote sensing techniques de_DE
dc.type Artikel de_DE
utue.quellen.id 20210824232002_01333
utue.personen.roh Ebrahimi-Khusfi, Zohre
utue.personen.roh Taghizadeh-Mehrjardi, Ruhollah
utue.personen.roh Kazemi, Mohamad
utue.personen.roh Nafarzadegan, Ali Reza
dcterms.isPartOf.ZSTitelID Atmospheric Pollution Research de_DE
dcterms.isPartOf.ZS-Issue Article 101064 de_DE
dcterms.isPartOf.ZS-Volume 12 de_DE
utue.fakultaet 07 Mathematisch-Naturwissenschaftliche Fakultät de_DE


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