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Parallel evolutionary multiobjective methodology for granularity and rule base learning in linguistic fuzzy systems
Bardallo J.M.
De Vega M.A.
Márquez F.A.
Peregrín A.
IEEE International Conference on Fuzzy Systems
Doi 10.1109/FUZZY.2009.5277343
páginas 1700 - 1705
2009-12-10
Citas: 4
Abstract
In this paper we present a parallel evolutionary multi-objective methodology for granularity and rule-based learning for Mamdani Fuzzy Systems. The proposed methodology produces a set of solutions with different trade-off between accuracy and interpretability, based on searching the number of labels and the fuzzy rules, and also makes a variable selection. This process is achieved by exploiting present parallel computer systems allowing it to deal with more complex models. ©2009 IEEE.
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