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Article

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Title

Optimization of Future Multifilter Surveys Toward Asteroid Characterization

Authors

[ 1 ] Instytut Informatyki, Wydział Informatyki i Telekomunikacji, Politechnika Poznańska | [ P ] employee

Scientific discipline (Law 2.0)

[2.3] Information and communication technology

Year of publication

2023

Published in

Astronomical Journal

Journal year: 2023 | Journal volume: vol. 166 | Journal number: no. 6

Article type

scientific article

Publication language

english

Keywords
EN
  • Asteroid surfaces
  • Spectroscopy
  • Multi-color photometry
Abstract

EN The aim of this paper is to find a set of photometric passbands that will give optimal results for spectrophotometric classification of asteroids into taxonomic types and classes. For this purpose various machine-learning methods are used, namely multinomial logistic regression, naive Bayes, support vector machines, gradient boosting, and multilayer perceptrons. Sequential feature selection is performed to assess the contribution of each reflectance difference. We find that to determine the taxonomic complexes with a balanced accuracy of 85%, a set of five spectrophotometric bands is required. For taxonomy type determination with the balanced accuracy of 80% a set of eight bands is necessary. Furthermore, only a three-band system is enough for distinguishing the C-complex asteroids with 92% balanced accuracy. These results can be used for designing future asteroid multifilter sky surveys.

Date of online publication

07.11.2023

Pages (from - to)

230-1 - 230-9

DOI

10.3847/1538-3881/acf459

URL

https://iopscience.iop.org/article/10.3847/1538-3881/acf459

Comments

Article Number: 230

License type

CC BY (attribution alone)

Open Access Mode

open journal

Open Access Text Version

final published version

Date of Open Access to the publication

at the time of publication

Ministry points / journal

140

Impact Factor

5,1

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