Intelligens szamitastechnikai modellek identifiacioja evolucios es gradiens alapu tanulo algoritmusokkal

Created by W.Langdon from gp-bibliography.bib Revision:1.7630

@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 = "Hungary",
• 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