Hierarchical fuzzy system modeling by Genetic and Bacterial Programming approaches
Created by W.Langdon from
gp-bibliography.bib Revision:1.8081
- @InProceedings{Balazs:2010:ieee-fuzz,
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author = "Krisztian Balazs and Janos Botzheim and
Laszlo T. Koczy",
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title = "Hierarchical fuzzy system modeling by Genetic and
Bacterial Programming approaches",
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booktitle = "IEEE International Conference on Fuzzy Systems
(FUZZ-IEEE 2010)",
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year = "2010",
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address = "Barcelona, Spain",
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month = "18-23 " # jul,
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pages = "1866--1871",
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publisher = "IEEE Press",
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keywords = "genetic algorithms, genetic programming",
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isbn13 = "978-1-4244-6920-8",
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URL = "http://www.cs.ucl.ac.uk/staff/W.Langdon/ftp/papers/botzheim/Balazs_2010_ieee-fuzz.pdf",
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DOI = "doi:10.1109/FUZZY.2010.5584220",
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size = "6 pages",
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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.",
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notes = "WCCI 2010. Also known as \cite{5584220}",
- }
Genetic Programming entries for
Krisztian Balazs
Janos Botzheim
Laszlo T Koczy
Citations