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 language | English (US) |
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Pages (from-to) | 10,847-10,865 |
Journal | Journal of geophysical research |
Volume | 99 |
Issue number | E5 |
DOIs | |
State | Published - 1994 |
Externally published | Yes |
ASJC Scopus subject areas
- Condensed Matter Physics
- Physical and Theoretical Chemistry
- Polymers and Plastics
- Materials Chemistry