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This work presents a hybrid fuzzy modeling approach based on the conditional fuzzy clustering algorithm, that aims to provide new means to handle the issue of interpretability of the rule base. The balance between interpretability and accuracy of fuzzy rules is addressed by means of the definition of contexts formed with a small number of input variables and the generation of clusters conditioned...
The dimension of a knowledge domain can impact the use of genetic algorithms to automatically design fuzzy rule bases, since the search space for the genetic algorithm increases exponentially with the number of features. Filters are a possible approach to reduce the number of features. However, the filter approach does not take into consideration the particular aspects of fuzzy logic when selecting...
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