Bio-Inspired Hybridization of Artificial Neural Networks: An Application for Mapping the Spatial Distribution of Soil Texture Fractions

dc.contributor.author	Taghizadeh-Mehrjardi, Ruhollah
dc.contributor.author	Scholten, Thomas
dc.date.accessioned	2022-07-26T11:09:15Z
dc.date.available	2022-07-26T11:09:15Z
dc.date.issued	2021
dc.identifier.issn	2072-4292
dc.identifier.uri	http://hdl.handle.net/10900/129752
dc.language.iso	en	de_DE
dc.publisher	Mdpi	de_DE
dc.relation.uri	http://dx.doi.org/10.3390/rs13051025	de_DE
dc.subject.ddc	550	de_DE
dc.subject.ddc	570	de_DE
dc.subject.ddc	600	de_DE
dc.subject.ddc	610	de_DE
dc.title	Bio-Inspired Hybridization of Artificial Neural Networks: An Application for Mapping the Spatial Distribution of Soil Texture Fractions	de_DE
dc.type	Article	de_DE
utue.quellen.id	20210512015105_00604
utue.personen.roh	Taghizadeh-Mehrjardi, Ruhollah
utue.personen.roh	Emadi, Mostafa
utue.personen.roh	Cherati, Ali
utue.personen.roh	Heung, Brandon
utue.personen.roh	Mosavi, Amir
utue.personen.roh	Scholten, Thomas
dcterms.isPartOf.ZSTitelID	Remote Sensing	de_DE
dcterms.isPartOf.ZS-Issue	Article 1025	de_DE
dcterms.isPartOf.ZS-Volume	13 (5)	de_DE
utue.fakultaet	07 Mathematisch-Naturwissenschaftliche Fakultät	de_DE