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.
Titolo: | A cluster analysis approach for rule base reduction |
Autori: | |
Data di pubblicazione: | 2019 |
Serie: | |
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. |
Handle: | http://hdl.handle.net/11587/438875 |
ISBN: | 978-3-319-95097-6 978-3-319-95098-3 |
Appare nelle tipologie: | Capitolo di Libro |
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