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Separated antecedent and consequent learning for Takagi-Sugeno fuzzy systems

Botzheim, Janos; Lughofer, Edwin; Klement, Erich Peter; Gedeon, Tamas (Tom); Koczy, Lazlo


In this paper a new algorithm for the learning of Takagi-Sugeno fuzzy systems is introduced. In the algorithm different learning techniques are applied for the antecedent and the consequent parameters of the fuzzy system. We propose a hybrid method for the antecedent parameters learning based on the combination of the Bacterial Evolutionary Algorithm (BEA) and the Levenberg-Marquardt (LM) method. For the linear parameters in fuzzy systems appearing in the rule consequents the Least Squares (LS)...[Show more]

CollectionsANU Research Publications
Date published: 2006
Type: Conference paper
Source: Proceedings 2006 IEEE International Conference on Fuzzy Systems
DOI: 10.1109/FUZZY.2006.1682014


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