Intelligens szamitastechnikai modellek identifiacioja evolucios es gradiens alapu tanulo algoritmusokkal

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

@PhdThesis{Botzheim:thesis,
  author =       "Janos Botzheim",
  title =        "Intelligens szamitastechnikai modellek identifiacioja
                 evolucios es gradiens alapu tanulo algoritmusokkal",
  school =       "Budapest University of Technology and Economics,
                 Faculty of Electrical Engineering and Informatics",
  type =         "{Ph.D.} thesis",
  year =         "2007",
  address =      "Budapest",
  month =        "11 " # nov,
  keywords =     "genetic algorithms, genetic programming",
  URL =          "http://www.sze.hu/~botzheim/hid/disszertacio.pdf",
  URL =          "http://www.cs.ucl.ac.uk/staff/W.Langdon/ftp/papers/botzheim/thesisbooklet.pdf",
  size =         "124 pages",
  abstract =     "The thesis discusses identification techniques of soft
                 computing models. Its goal is to develop identification
                 methods based on numerical data that can produce
                 results better in terms of quality criteria (e.g. mean
                 square error) relevant for the given applications than
                 other techniques known from the literature. The first
                 statement proposes the Bacterial Evolutionary Algorithm
                 for the extraction of Mamdani-type fuzzy rules with
                 trapezoidal membership functions. The second statement
                 proposes the application of the Levenberg-Marquardt
                 algorithm for local optimisation of fuzzy rules. The
                 third statement introduces the Bacterial Memetic
                 Algorithm, a combination of the Bacterial Evolutionary
                 and the Levenberg-Marquardt algorithm. The fourth
                 statement deals with Takagi-Sugeno-type fuzzy systems.
                 The fifth statement proposes a new technique called
                 Bacterial Programming for the design process of
                 B-spline neural networks. Finally, the sixth statement
                 presents the application of Bacterial Evolutionary
                 Algorithm for the feature selection problem.",
  notes =        "In Hungarian. 24 page english summary",
}

Genetic Programming entries for Janos Botzheim

Citations