Improving the performance of fuzzy rule-based classification systems with interval-valued fuzzy sets and genetic amplitude tuning

Information Sciences

Volumn 180, Issue 19, 2010, Pages 3674-3685

  Sanz, José Antonio ^a   Fernández, Alberto ^b   Bustince, Humberto ^a   Herrera, Francisco ^c  

^a PUBLIC UNIVERSITY OF NAVARRE   (Spain)

^b UNIVERSITY OF JAÉN   (Spain)

^c UNIVERSITY OF GRANADA   (Spain)

Author keywords

Fuzzy rule based classification systems; Genetic algorithms; Interval valued fuzzy sets; Tuning

Indexed keywords

ARTIFICIAL INTELLIGENCE; CLASSIFICATION (OF INFORMATION); FUZZY INFERENCE; FUZZY RULES; FUZZY SETS; GENETIC ALGORITHMS; KNOWLEDGE BASED SYSTEMS; LEARNING SYSTEMS; TUNING;

COMPUTATIONAL INTELLIGENCE TECHNIQUES; EMPIRICAL STUDIES; FUZZY PARTITION; FUZZY RULE BASED CLASSIFICATION SYSTEMS; FUZZY RULE LEARNING; INTERVAL-VALUED FUZZY SETS; LINGUISTIC VARIABLE; POST PROCESSING;

LEARNING ALGORITHMS;

EID: 77958453890     PISSN: 00200255     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.ins.2010.06.018     Document Type: Article

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