Identification of Fuzzy Models Using Cartesian Genetic Programming

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@InProceedings{Yazdani:2008:CIS,

• author = "S. Yazdani and M. {Aliyari shoorehdeli} and M. Teshnehlab",
• title = "Identification of Fuzzy Models Using Cartesian Genetic Programming",
• booktitle = "International Conference on Computational Intelligence and Security, CIS '08",
• year = "2008",
• month = dec,
• volume = "2",
• pages = "76--81",
• 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",
• DOI = "doi:10.1109/CIS.2008.143",
• 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.",
• notes = "Also known as \cite{4724740}",

}

Genetic Programming entries for Samaneh Yazdani Mahdi Aliyari shoorehdeli Mohammad Teshnehlab

Citations