Genetic Algorithms Applied to Spectral Index Extraction

  • Diego Ordóñez
  • Carlos Dafonte
  • Minia Manteiga
  • Bernardino Arcay
Conference paper
Part of the Studies in Computational Intelligence book series (SCI, volume 343)


Within the scope of computational astropysics, this work presents an experimental study on the application of genetic algorithms to the automated extraction of relevant information from stellar spectra. The input data are a dataset obtained through the collaboration of our research group with the Gaia project of the European Space Agency. The results show that predictions based on spectral indices, which in turn were extracted by means of genetic algorithms, have accuracy levels that are very similar to those obtained through wavelength information. Working with a reduced dataset also implies the reduction of complexity and increased performance.


Genetic algorithm Artificial neural network Connectionist systems FFT Wavelet transform GAIA mission Stellar spectra Stellar parameters 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Diego Ordóñez
    • 1
  • Carlos Dafonte
    • 1
  • Minia Manteiga
    • 2
  • Bernardino Arcay
    • 1
  1. 1.Information and Communications Technologies Department, Faculty of Computer ScienceUniversity of La CoruñaA CoruñaSpain
  2. 2.Department of Navigation and Earth SciencesUniversity of A CoruñaA CoruñaSpain

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