Model Identification by Bacterial Optimization

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  title =        "Model Identification by Bacterial Optimization",
  author =       "J. Botzheim and L. T. Koczy",
  booktitle =    "Proceedings of the 5th International Symposium of
                 Hungarian Researchers on Computational Intelligence",
  year =         "2004",
  pages =        "91--102",
  address =      "Budapest, Hungary",
  month =        nov,
  keywords =     "genetic algorithms, genetic programming",
  URL =          "",
  URL =          "",
  bibsource =    "OAI-PMH server at",
  contributor =  "CiteSeerX",
  language =     "en",
  oai =          "oai:CiteSeerXPSU:",
  abstract =     "In the field of control systems it is common to use
                 techniques based on model adaptation to carry out
                 control for plants for which mathematical analysis may
                 be intricate. Increasing interest in biologically
                 inspired learning algorithms for control techniques
                 such as artificial neural networks and fuzzy systems is
                 in progress. In this paper a recent kind of
                 evolutionary method called bacterial algorithm is
                 introduced. This method can be used for fuzzy rule
                 extraction and optimization. Bacterial Programming is
                 also proposed in this paper. This approach is the
                 combination of the bacterial algorithm and the genetic
                 programming techniques and can be applied for the
                 optimization of the structure of Bspline neural

Genetic Programming entries for Janos Botzheim Laszlo T Koczy