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# Fuzzy classes

FuzzyLib provides a set of classes for building fuzzy inference engines. Available are fuzzy sets, fuzzy variables, and a inference engine based on fuzzy rules. The membership values are normalized ( by default ), but can be changed to max and min values in different classes. All fuzzy sets and functions are realized with crisply defined membership values ( type 1 fuzzy sets and functions ).
Currently prod-min inference is used and a center-of-gravity output defuzzification. This will be extended in a future release, providing different operators for aggregation, inference, and accumulation. Up to now two different fuzzy set representations are implemented: LR-representation and arrays.

For more information about fuzzy logic see:
Zimmermann,. H.-J. [1991]. Fuzzy Set Theory And Its Applications. Kluwer Accademic Publishers.
Additionally, the FAQ of the newsgroup "comp.ai.fuzzy" should be recommended in this context.

Links to more information about fuzzy logic:

- Fuzzy Logic Lab Linz
- Fuzzy Logic Archive at Quadralay Corporation
- FAQ - Fuzzy Logic and Fuzzy Expert Systems
- Center for Fuzzy Logic and Intelligent Systems Research (CFL) - Fuzzy Logic Research Center in Texas A&M University.

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