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

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	Article	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