Evolving flexible beta basis function neural tree using extended genetic programmin \& Hybrid Artificial Bee Colony

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@Article{Bouaziz:2016:ASC,
  author =       "Souhir Bouaziz and Habib Dhahri and Adel M. Alimi and 
                 Ajith Abraham",
  title =        "Evolving flexible beta basis function neural tree
                 using extended genetic programmin \& Hybrid Artificial
                 Bee Colony",
  journal =      "Applied Soft Computing",
  year =         "2016",
  ISSN =         "1568-4946",
  DOI =          "doi:10.1016/j.asoc.2016.03.006",
  URL =          "http://www.sciencedirect.com/science/article/pii/S1568494616301156",
  abstract =     "In this paper, a new hybrid learning algorithm is
                 introduced to evolve the flexible beta basis function
                 neural tree (FBBFNT). The structure is developed using
                 the Extended Genetic Programming (EGP) and the Beta
                 parameters and connected weights are optimized by the
                 Hybrid Artificial Bee Colony algorithm. This
                 hybridization is essentially based on replacing the
                 random Artificial Bee Colony (ABC) position with the
                 guided Opposite-based Particle Swarm Optimization
                 (OPSO) position. Such modification can minimize the
                 delay which might be lead by the random position, in
                 reaching the global solution. The performance of the
                 proposed model is evaluated for benchmark problems
                 drawn from time series prediction area and is compared
                 with those of related methods.",
  keywords =     "genetic algorithms, genetic programming, Flexible beta
                 basis function neural tree model, Hybrid Artificial Bee
                 Colony algorithm, Time-series forecasting",
}

Genetic Programming entries for Souhir Bouaziz Habib Dhahri Adel M Alimi Ajith Abraham

Citations