Abstract
This paper describes the formulation and development of STARMIND, a hybrid system devoted to the automated classification of stellar spectra in the MK system. The MK system is an astronomical classification system used to cluster stars in morphological types based on stellar temperatures and luminosities. Our hybrid system is composed by a knowledge-based system that performs the first taxonomy in stellar types. A second-level system is based on Artificial Neural Networks and performs a more refined classification in stellar subtypes. Artificial Neural Networks were defined by selecting the optimal algorithms for training and architecture for each of the stellar spectra subtypes.
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