Learning Fuzzy Rules from Data

نویسندگان

  • Frank Klawonn
  • Annette Keller
چکیده

This paper brieey reviews techniques for learning fuzzy rules. In many applications fuzzy if-then rules are not interpreted as implications , but in a procedural way that corresponds to a conjunction or Cartesian product. For this type of rules many approaches to rule learning have been proposed. However, for more complex fuzzy systems based on logical implications, there is still a need for suitable learning algorithms .

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تاریخ انتشار 2007