Simplifying fuzzy rule-based models using orthogonal transformation methods

Abstract

An important issue in fuzzy-rule-based modeling is how to select a set of important fuzzy rules from a given rule base. Even though it is conceivable that removal of redundant or less important fuzzy rules from the rule base can result in a compact fuzzy model with better generalizing ability, the decision as to which rules are redundant or less important… (More)
DOI: 10.1109/3477.740162

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