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https://scidar.kg.ac.rs/handle/123456789/10646
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DC Field | Value | Language |
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dc.rights.license | openAccess | - |
dc.contributor.author | Vujičić, Dejan | - |
dc.contributor.author | Pavlovic, Radisa | - |
dc.contributor.author | Milošević, Danijela | - |
dc.contributor.author | Dordević Borislav | - |
dc.contributor.author | Randjić, Siniša | - |
dc.contributor.author | Stojić, Dijana | - |
dc.date.accessioned | 2021-04-20T16:17:25Z | - |
dc.date.available | 2021-04-20T16:17:25Z | - |
dc.date.issued | 2020 | - |
dc.identifier.issn | 1450-698X | - |
dc.identifier.uri | https://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.rights | info:eu-repo/semantics/openAccess | - |
dc.rights.uri | https://creativecommons.org/licenses/by-nc-nd/4.0/ | - |
dc.source | Serbian Astronomical Journal | - |
dc.title | CLASSIFICATION OF ASTEROID FAMILIES WITH ARTIFICIAL NEURAL NETWORKS | - |
dc.type | article | - |
dc.identifier.doi | 10.2298/SAJ2001039V | - |
dc.identifier.scopus | 2-s2.0-85099987946 | - |
Appears in Collections: | Faculty of Technical Sciences, Čačak |
Files in This Item:
File | Description | Size | Format | |
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10.2298-SAJ2001039V.pdf | 1.28 MB | Adobe PDF | View/Open |
This item is licensed under a Creative Commons License