Identification of Fuzzy Models Using Cartesian Genetic Programming
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- @InProceedings{Yazdani:2008:CIS,
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author = "S. Yazdani and M. {Aliyari shoorehdeli} and
M. Teshnehlab",
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title = "Identification of Fuzzy Models Using Cartesian Genetic
Programming",
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booktitle = "International Conference on Computational Intelligence
and Security, CIS '08",
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year = "2008",
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month = dec,
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volume = "2",
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pages = "76--81",
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keywords = "genetic algorithms, genetic programming, Cartesian
genetic programming, complex optimization problem,
fuzzy clustering, fuzzy models, membership function
parameters, pattern recognition, recursive least
square, combinatorial mathematics, fuzzy set theory,
fuzzy systems, least squares approximations, pattern
clustering, recursive estimation",
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DOI = "doi:10.1109/CIS.2008.143",
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abstract = "Fuzzy models have capability for solving problem in
different application such as pattern recognition,
prediction and control. Nevertheless, it has to be
emphasized that the identification of a fuzzy model is
complex task with many local minima. Cartesian genetic
programming provides a way to solve such complex
optimization problem. In this paper, fuzzy model is in
form of network. Cartesian genetic programming is used
to optimize the antecedent part and recursive least
square is used to optimized the consequent part. The
initialization of membership function parameters are
doing with fuzzy clustering. Benefit of the methodology
is illustrated by simulation results.",
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notes = "Also known as \cite{4724740}",
- }
Genetic Programming entries for
Samaneh Yazdani
Mahdi Aliyari shoorehdeli
Mohammad Teshnehlab
Citations