Recurrent Cartesian Genetic Programming of Artificial Neural Networks

Created by W.Langdon from gp-bibliography.bib Revision:1.3973

@Article{Turner:2016:GPEM,
  author =       "Andrew James Turner and Julian Francis Miller",
  title =        "Recurrent Cartesian Genetic Programming of Artificial
                 Neural Networks",
  journal =      "Genetic Programming and Evolvable Machines",
  year =         "2017",
  volume =       "18",
  number =       "2",
  pages =        "185--212",
  month =        jun,
  keywords =     "genetic algorithms, genetic programming, Cartesian
                 Genetic Programming, ANN, NeuroEvolution, Forecasting",
  ISSN =         "1389-2576",
  DOI =          "doi:10.1007/s10710-016-9276-6",
  size =         "28 pages",
  abstract =     "Cartesian Genetic Programming of Artificial Neural
                 Networks is a NeuroEvolutionary method based on
                 Cartesian Genetic Programming. Cartesian Genetic
                 Programming has recently been extended to allow
                 recurrent connections. This work investigates applying
                 the same recurrent extension to Cartesian Genetic
                 Programming of Artificial Neural Networks in order to
                 allow the evolution of recurrent neural networks. The
                 new Recurrent Cartesian Genetic Programming of
                 Artificial Neural Networks method is applied to the
                 domain of series forecasting where it is shown to
                 significantly outperform all standard forecasting
                 techniques used for comparison including autoregressive
                 integrated moving average and multilayer perceptrons.
                 An ablation study is also performed isolating which
                 specific aspects of Recurrent Cartesian Genetic
                 Programming of Artificial Neural Networks contribute to
                 it's effectiveness for series forecasting.",
}

Genetic Programming entries for Andrew James Turner Julian F Miller

Citations