Artificial neural networks generation using grammatical evolution

Created by W.Langdon from gp-bibliography.bib Revision:1.4504

  author =       "Khabat Soltanian and Fardin Akhlaghian Tab and 
                 Fardin Ahmadi Zar and Ioannis Tsoulos",
  title =        "Artificial neural networks generation using
                 grammatical evolution",
  booktitle =    "21st Iranian Conference on Electrical Engineering
                 (ICEE 2013)",
  year =         "2013",
  address =      "Mashhad, Iran",
  month =        "14-16 " # may,
  publisher =    "IEEE",
  keywords =     "genetic algorithms, genetic programming, grammatical
                 evolution, artificial neural networks, evolutionary
                 computing, classification problems",
  ISSN =         "2164-7054",
  DOI =          "doi:10.1109/IranianCEE.2013.6599788",
  size =         "5 pages",
  abstract =     "in this paper an automatic artificial neural network
                 generation method is described and evaluated. The
                 proposed method generates the architecture of the
                 network by means of grammatical evolution and uses back
                 propagation algorithm for training it. In order to
                 evaluate the performance of the method, a comparison is
                 made against five other methods using a series of
                 classification benchmarks. In the most cases it shows
                 the superiority to the compared methods. In addition to
                 the good experimental results, the ease of use is
                 another advantage of the method since it works with no
                 need of experts.",
  notes =        "Also known as \cite{6599788}",

Genetic Programming entries for Khabat Soltanian Fardin Akhlaghian Tab Fardin Ahmadizar Ioannis G Tsoulos