Classification of asteroid spectra using a neural network

E. S. Howell, E. Merenyi, L. A. Lebofsky

Research output: Contribution to journalArticlepeer-review

79 Scopus citations

Abstract

The 52-color asteroid survey (Bell et al., 1988) together with the 8-color asteroid survey (Zellner et al., 1985) provide a data set of asteroid spectra spanning 0.3-2.5μm. An artificial neural network clusters these asteroid spectra based on their similarity to each other. The neural network has also been trained with a categorization learning output layer in a supervised mode to associate the established clusters with taxonomic classes. Results of this classification agree with Tholen's classification based on the 8-color data alone. When extending the spectral range using the 52-color survey data, it is found that some modification of the Tholen classes is indicated to produce a cleaner, self-consistent set of taxonomic classes. -from Authors

Original languageEnglish (US)
Pages (from-to)10,847-10,865
JournalJournal of geophysical research
Volume99
Issue numberE5
DOIs
StatePublished - 1994
Externally publishedYes

ASJC Scopus subject areas

  • Condensed Matter Physics
  • Physical and Theoretical Chemistry
  • Polymers and Plastics
  • Materials Chemistry

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