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Context Adaptation of Mamdani Fuzzy Systems through New Operators Tuned by a Genetic Algorithm

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3 Author(s)
Botta, A. ; IMT Lucca Inst. for Adv. Studies, Lucca ; Lazzerini, B. ; Marcelloni, F.

Context adaptation can be achieved by adjusting an initial normalized fuzzy rule-based system through the use of operators that appropriately change the representation of the linguistic variables. The choice of the specific operators and their parameters should be context-based and optimized so as to obtain a good interpretability-accuracy tradeoff. In this paper we propose a set of context adaptation operators that, starting from a given fuzzy system, adjust some of its component!, such as fuzzy set support and core, membership function shape, etc. We use a genetic tuning process for choosing the operator parameters. We finally describe the application of the proposed operators to Mamdani fuzzy systems with reference to two real examples.

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Fuzzy Systems, 2006 IEEE International Conference on

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