Hierarchical fuzzy system modeling by Genetic and Bacterial Programming approaches

Created by W.Langdon from gp-bibliography.bib Revision:1.8129

@InProceedings{Balazs:2010:ieee-fuzz,

• author = "Krisztian Balazs and Janos Botzheim and Laszlo T. Koczy",
• title = "Hierarchical fuzzy system modeling by Genetic and Bacterial Programming approaches",
• booktitle = "IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2010)",
• year = "2010",
• address = "Barcelona, Spain",
• month = "18-23 " # jul,
• pages = "1866--1871",
• publisher = "IEEE Press",
• keywords = "genetic algorithms, genetic programming",
• isbn13 = "978-1-4244-6920-8",
• URL = "http://www.cs.ucl.ac.uk/staff/W.Langdon/ftp/papers/botzheim/Balazs_2010_ieee-fuzz.pdf",
• DOI = "doi:10.1109/FUZZY.2010.5584220",
• size = "6 pages",
• abstract = "In this paper a method is proposed for constructing hierarchical fuzzy rule bases in order to model black box systems defined by input-output pairs, i.e. to solve supervised machine learning problems. The resultant hierarchical rule base is the knowledge base, which is constructed by using structure constructing evolutionary techniques, namely, Genetic and Bacterial Programming Algorithms. Applying hierarchical fuzzy rule bases is a way of reducing the complexity of the knowledge base, whereas evolutionary methods ensure a relatively efficient learning process. This is the reason of the investigation of this combination.",
• notes = "WCCI 2010. Also known as \cite{5584220}",

}

Genetic Programming entries for Krisztian Balazs Janos Botzheim Laszlo T Koczy

Citations