In this paper we propose an iterative algorithm for fuzzy rule base simplification based on cluster analysis. The proposed approach uses a dissimilarity measure that allows to assign different importance to values and ambiguities of fuzzy terms in antecedent and consequent parts of fuzzy rules.

A cluster analysis approach for rule base reduction

Giove S.;
2019-01-01

Abstract

In this paper we propose an iterative algorithm for fuzzy rule base simplification based on cluster analysis. The proposed approach uses a dissimilarity measure that allows to assign different importance to values and ambiguities of fuzzy terms in antecedent and consequent parts of fuzzy rules.
2019
Neural Advances in Processing Nonlinear Dynamic Signals
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10278/3702516
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