Artificial Neural Networks as a Tool for Prognosis of Chemical and Mineral Composition of Lunar Soils from Spectral Measurements
Abstract
We compared two statistical techniques (Multiple Linear Regression and Artificial Neural Networks) for prognosis of lunar surface composition using the LSCC data. The results may be a useful for analysis of data obtained from SMART-1 and Chandrayaan missions.
- Publication:
-
37th Annual Lunar and Planetary Science Conference
- Pub Date:
- March 2006
- Bibcode:
- 2006LPI....37.1280K