Predicting Maximum Circular Velocity in a sample of MaNGA galaxies using artificial intelligenceDownload PDF

Jul 30, 2019RIIAA 2019 Conference SubmissionReaders: Everyone
  • Keywords: Galaxy, prediction, catalog, sample, deep learning, machine learning
  • TL;DR: Artificial Intelligence apply to predict galaxy properties.
  • Abstract: We use artificial intelligence algorithms to predict the Vmax (Maximum circular velocity) value in a galaxy sample of 200 resolved MaNGA and CALIFA galaxies with velocity fields, using different properties, like stellar mass, circular velocity at effective radius and star formation rate to build the training sample. Here we present the predicted results from apply a Random Forest algorithm and a Cross validated artificial neural network to our sample.
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