System Identification Using Genetic Algorithms

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

  author =       "Jana Nowakova and Miroslav Pokorny",
  title =        "System Identification Using Genetic Algorithms",
  booktitle =    "Proceedings of the Fifth International Conference on
                 Innovations in Bio-Inspired Computing and Applications
                 IBICA 2014",
  year =         "2014",
  editor =       "Pavel K{\"o}mer and Ajith Abraham and 
                 V{\'a}clav Sn{\'a}{\v{s}}el",
  volume =       "303",
  series =       "Advances in Intelligent Systems and Computing",
  pages =        "413--418",
  address =      "Ostrava, Czech Republic",
  month =        "23-24 " # jun,
  publisher =    "Springer",
  keywords =     "genetic algorithms, genetic programming,
                 Identification, optimization, system",
  URL =          "",
  affiliation =  "Department of Cybernetics and Biomedical Engineering,
                 VSB-Technical University of Ostrava, 17. listopadu
                 15/2172, 708 33 Ostrava, Poruba, Czech Republic",
  DOI =          "doi:10.1007/978-3-319-08156-4_41",
  abstract =     "System identification is one of the necessary tasks in
                 controller design and its adaptation. Many
                 identification methods are known, and new ones are
                 still being developed in order to find a better
                 solution for huge scale of cases. In the paper
                 identification of system of 2nd order systems using
                 genetic algorithms is demonstrated. In presented case
                 genetic algorithms are used for finding parameters of
                 difference equation of the controlled system and it
                 substitutes classic, conventional optimization methods.
                 Proposed method can be used for continuous
                 identification or it can be activated in defined time
                 points on stored data. And on the other hand, presented
                 task is also a case of a specific usage of genetic
                 algorithms and it can serve as a proof of efficiency of
                 this non-conventional optimization method (simulated in
                 the Matlab&Simulink software environment).",
  source =       "Scopus",

Genetic Programming entries for Jana Nowakova Miroslav Pokorny