In this paper we introduce a set of tuning operators that allow us to implement context adaptation of fuzzy rule-based systems while keeping semantics and interpretability. The idea is to achieve context adaptation by starting from a (possibly generic) fuzzy system and adjusting one or more its components, such as membership function shape, fuzzy set support, distribution of membership functions, etc. We make use of a genetic optimization process to appropriately choose the operator parameters. Finally, we show the application of the proposed operators to Mamdani fuzzy systems.
New Operators for Context Adaptation of Mamdani Fuzzy Systems
LAZZERINI, BEATRICE;MARCELLONI, FRANCESCO
2006-01-01
Abstract
In this paper we introduce a set of tuning operators that allow us to implement context adaptation of fuzzy rule-based systems while keeping semantics and interpretability. The idea is to achieve context adaptation by starting from a (possibly generic) fuzzy system and adjusting one or more its components, such as membership function shape, fuzzy set support, distribution of membership functions, etc. We make use of a genetic optimization process to appropriately choose the operator parameters. Finally, we show the application of the proposed operators to Mamdani fuzzy systems.File in questo prodotto:
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