New operators for context adaptation of Mamdani fuzzy systems

被引：2

作者：

Botta, Alessio ^{[1
]}

Lazzerini, Beatrice ^{[2
]}

Marcelloni, Francesco ^{[2
]}

机构：

[1] IMT, Lucca Inst Adv Studies, Via San Micheletto 3, I-55100 Lucca, Italy

[2] Dipartimento Ingn Informaz, I-56122 Pisa, Italy

来源：

APPLIED ARTIFICIAL INTELLIGENCE | 2006年

关键词：

D O I：

10.1142/9789812774118_0009

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

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.

引用

页码：35 / +

页数：2