1. University of Kragujevac Digital Archive
  2. University of Kragujevac
  3. Faculty of Technical Sciences, Čačak
Please use this identifier to cite or link to this item: https://scidar.kg.ac.rs/handle/123456789/10646
Full metadata record
DC FieldValueLanguage
dc.rights.licenseBY-NC-ND-
dc.contributor.authorVujičić, Dejan-
dc.contributor.authorPavlovic, Radisa-
dc.contributor.authorMilošević, Danijela-
dc.contributor.authorDordević Borislav-
dc.contributor.authorRandjić, Siniša-
dc.contributor.authorStojić, Dijana-
dc.date.accessioned2021-04-20T16:17:25Z-
dc.date.available2021-04-20T16:17:25Z-
dc.date.issued2020-
dc.identifier.issn1450-698X-
dc.identifier.urihttps://scidar.kg.ac.rs/handle/123456789/10646-
dc.description.abstract© 2020. The Author(s). Published by Astronomical Observatory of Belgrade and Faculty of Mathematics, University of Belgrade. This open access article is distributed under CC BY-NC-ND 4.0 International licence. All Rights Reserved. This paper describes an artificial neural network for classification of asteroids into families. The data used for artificial neural network training and testing were obtained by the Hierarchical Clustering Method (HCM). We have shown that an artificial neural networks can be used as a validation method for the HCM on families with a large number of members.-
dc.rightsopenAccess-
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/-
dc.sourceSerbian Astronomical Journal-
dc.titleCLASSIFICATION OF ASTEROID FAMILIES WITH ARTIFICIAL NEURAL NETWORKS-
dc.typearticle-
dc.identifier.doi10.2298/SAJ2001039V-
dc.identifier.scopus2-s2.0-85099987946-
Appears in Collections:Faculty of Technical Sciences, Čačak

Page views(s)

123

Downloads(s)

9

Files in This Item:
File Description SizeFormat 
10.2298-SAJ2001039V.pdf1.28 MBAdobe PDFThumbnail
View/Open
Show simple item record


This item is licensed under a Creative Commons License Creative Commons