Genetic programming tuned fuzzy controlled traffic light system

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

@InProceedings{Padmasiri:2014:ICTer,
  author =       "T. D. N. D. Padmasiri and D. N. Ranasinghe",
  booktitle =    "2014 International Conference on Advances in ICT for
                 Emerging Regions (ICTer)",
  title =        "Genetic programming tuned fuzzy controlled traffic
                 light system",
  year =         "2014",
  pages =        "91--95",
  abstract =     "A blend of fuzzy logic and genetic programming is used
                 in this research to achieve a single fine-tuned fuzzy
                 rule, upon giving hundreds of fuzzy rules as the input.
                 The system has Poisson arrival rate of vehicles, and
                 decisions are taken to alter the sequence of lights
                 based on the queue lengths of the lanes. The traffic
                 simulator handles routing of vehicles in a single
                 four-leg intersection with left and right turns. The
                 fuzzy logic traffic controller system is used to
                 generate the simulation data to feed the genetic
                 programming system. The genetic programming system then
                 creates an optimum fuzzy rule. This fine-tuned fuzzy
                 rule is proven to be qualitatively better with respect
                 to the mean square queue length and its error of the
                 total system at any given point of time.",
  keywords =     "genetic algorithms, genetic programming",
  DOI =          "doi:10.1109/ICTER.2014.7083885",
  month =        dec,
  notes =        "Also known as \cite{7083885}",
}

Genetic Programming entries for T D N D Padmasiri D N Ranasinghe

Citations