Classification of asteroid families with artificial neural networks

Vujicic, Dejan; Pavlović, R.; Milošević, Dušan; Djordjevic, Borislav; Randjic, Sinisa; Stojic, Dijana

doi:10.2298/saj2001039v

Cited by 4 publications

(2 citation statements)

References 17 publications

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“…In this region, however, even the traditional HCM is still applicable due to the significantly smaller number of objects than the main belt's low-inclination part. Vujičić et al (2020) explored the possibility of using an artificial neural network (ANN) for the classification of asteroids into families. The obtained results showed that the ANNbased algorithm performs somewhat better than the clustering algorithms tested by .…”

Section: Machine Learning-based Methodologymentioning

confidence: 99%

“…A possible solution to deal with a large amount of data for the purpose of classification of asteroids into families could be a multi-step methodology proposed by Milani et al (2014, see also Milani et al 2016. Alternatively, the problem could be treated by employing machine learningbased tools, which can be used either to identify new asteroid families Vujičić et al 2020), or to attach new members to known families (Carruba et al 2020a).…”

Section: Recent Advances In Asteroid Family Identificationmentioning

confidence: 99%

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Asteroid families: properties, recent advances, and future opportunities

Novaković

Vokrouhlický

Spoto

et al. 2022

Celest Mech Dyn Astron

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Collisions are one of the key processes shaping planetary systems. Asteroid families are outcomes of such collision still identifiable across our solar system. The families provide a unique view of catastrophic disruption phenomena and have been in the focus of planetary scientists for more than a century. Most of them are located in the main belt, a ring of asteroids between Mars and Jupiter. Here we review the basic properties of the families, discuss some recent advances, and anticipate future challenges. This review pays more attention to dynamic aspects such as family identification, age determination, and long-term evolution. The text, however, goes beyond that. Especially, we cover the details of young families that see the major advances in the last years, and we anticipate it will develop even faster in the future. We also discuss the relevance of asteroid families for water-ice content in the asteroid belt and our current knowledge on links between families and main-belt comets. query Please check the edit made in the article title.

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Section: Machine Learning-based Methodologymentioning

confidence: 99%