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• W2093627519 abstract "The performance of a fuzzy controller is determined in a great amount by the underlying rule base. In this paper, we present tuning methods implemented in our rule base identification and tuning toolbox. The toolbox is easy-to-use Matlab based software with graphical user interface. All the implemented tuning methods support the creation of low complexity and compact rule bases that contain only the most relevant rules. Besides, the clonal selection based method also can be applied in case of covering rule bases as well as for the tuning of input/output gains of fuzzy controllers." @default.
• W2093627519 created "2016-06-24" @default.
• W2093627519 creator A5007603867 @default.
• W2093627519 creator A5068465319 @default.
• W2093627519 date "2014-06-01" @default.
• W2093627519 modified "2023-09-26" @default.
• W2093627519 title "Rule base identification toolbox for fuzzy controllers" @default.
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• W2093627519 doi "https://doi.org/10.1109/cisti.2014.6877094" @default.
• W2093627519 hasPublicationYear "2014" @default.
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