Determination of stellar fundamental parameters using Artificial Intelligence techniques. Luis M. Sarro. Dpto. Inteligencia Artificial, UNED / Spanish VO, Madrid, Spain Enrique Solano. INTA-LAEFF / Spanish VO, P.O. Box 50727, Madrid, Spain Determination of stellar fundamental parameters using Artificial Intelligence techniques. Luis M. Sarro. Dpto. Inteligencia Artificial, UNED / Spanish VO, Madrid, Spain Enrique Solano. INTA-LAEFF / Spanish VO, P.O. Box 50727, Madrid, Spain Understanding the physical processes of stars requires the determination of a number of fundamental parameter. The advances in astronomical instrumentation as well as in computational capabilities have provided the means to make, for the first time, accurate and precise comparisons between extensive libraries of synthetic spectra and large observational databases covering wide wavelength ranges at high resolutions. In this framework the classical methodology, where a high degree of human intervention is present, has proven to be quite inappropriate and automatic methods constitute the only approach to guarantee repeatability and high speed in the determination of the stellar fundamental parameters. In this poster we describe the techniques used for the determination of the effective temperature, surface gravity, metallicity and projected rotational velocity of the star with planet HD142. A comparison with the results obtained by different authors using detailed analysis demonstrates the potential capabilities of our methodology. Methodology and Results + Bayesian ensemble of Artificial Neural Networks Determinations from detailed analysis Bayesian inference ReferenceMethod Teff (K) logg[M/H]vsini Santos et al.Spectra 6302 ± ± ±0.07 Nordstrom et al. Strömgren phot Solano et al.Spectra 6384 ± ± ± ±2 Ribas et al.VJHK phot ±65 Determination of stellar physical parameters in the framework of the Virtual Observatory A critical issue to ensure efficiency in the determination of the stellar parameters from spectroscopy is the accessibility of the theoretical models. In the context of the Virtual Observatory, the Spanish VO is playing a leading role in the definition (in collaboration with ESA-VO) and implementation of VO- compliant access protocols for theoretical datasets, in particular for stellar model atmospheres. We have already implemented a VO access protocol for the ATLAS9 Kurucz model atmospheres and we are in contact with a number of developers and publishers of libraries of synthetic stellar spectra for their adaptation to the Virtual Observatory standards and requirements. In a medium term, our system will be implemented as a web service allowing the user to choose in a straightforward way the theoretical models and/or libraries with which to compare the observations. REFERENCES Hobson, Bridle & Lahav, 2002, MNRAS, 335, Hornik, Stinchcombe & H. White, 1989, Neural Networks, 2, Comparison between the observed spectrum and the best model.