English

AI Gamma-Ray Burst Classification: Methodology/Preliminary Results

Astrophysics 2009-10-30 v1

Abstract

Artificial intelligence (AI) classifiers can be used to classify unknowns, refine existing classification parameters, and identify/screen out ineffectual parameters. We present an AI methodology for classifying new gamma-ray bursts, along with some preliminary results.

Keywords

Cite

@article{arxiv.astro-ph/9712077,
  title  = {AI Gamma-Ray Burst Classification: Methodology/Preliminary Results},
  author = {Jon Hakkila and David J. Haglin and Richard J. Roiger and Robert S. Mallozzi and Geoffrey N. Pendleton and Charles A. Meegan},
  journal= {arXiv preprint arXiv:astro-ph/9712077},
  year   = {2009}
}

Comments

5 pages, 2 postscript figures. To appear in the Fourth Huntsville Gamma-Ray Burst Symposium

R2 v1 2026-07-22T09:37:15.293Z