Identifying fuzzy models utilizing genetic programming
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- @Article{Bastian:2000:FSS,
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author = "Andreas Bastian",
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title = "Identifying fuzzy models utilizing genetic
programming",
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journal = "Fuzzy Sets and Systems",
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volume = "113",
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pages = "333--350",
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year = "2000",
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number = "3",
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month = "1 " # aug,
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keywords = "genetic algorithms, genetic programming, System
identification, Fuzzy modeling",
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URL = "http://www.sciencedirect.com/science/article/B6V05-4234BFC-1/1/261a04fa056f3f0dfe0fb79a773a971a",
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abstract = "Fuzzy models offer a convenient way to describe
complex nonlinear systems. Moreover, they permit the
user to deal with uncertainty and vagueness. Due to
these advantages fuzzy models are employed in various
fields of applications, e.g. control, forecasting, and
pattern recognition. Nevertheless, it has to be
emphasised that the identification of a fuzzy model is
a complex optimisation task with many local minima.
Genetic programming provides a way to solve such
complex optimization problems. In this work, the use of
genetic programming to identify the input variables,
the rule base and the involved membership functions of
a fuzzy model is proposed. For this purpose, several
new reproduction operators are introduced.",
- }
Genetic Programming entries for
Andreas Bastian
Citations