Abstract
Fuzzy systems meant here as rule-based or knowledge-based systems. These systems consist of a knowledge base and a reasoning mechanism called fuzzy inference engine. A fuzzy rule base consists of a collection of fuzzy if-then rules. A fuzzy inference engine combines these rules into a mapping from the inputs of the system into its output, using fuzzy reasoning methods (see Chapter 2). The fuzzy systems can take either fuzzy sets or crisp values as inputs. In the latter case, we use a fuzzifier at the system input. Fuzzy systems produce a fuzzy set as output. In some applications we need real-valued output. To extract crisp value from the output fuzzy set defuzzification methods are used (see Section 2.9).
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© 2000 Physica-Verlag Heidelberg
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Czogała, E., Łęski, J. (2000). Fuzzy systems. In: Fuzzy and Neuro-Fuzzy Intelligent Systems. Studies in Fuzziness and Soft Computing, vol 47. Physica, Heidelberg. https://doi.org/10.1007/978-3-7908-1853-6_5
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DOI: https://doi.org/10.1007/978-3-7908-1853-6_5
Publisher Name: Physica, Heidelberg
Print ISBN: 978-3-662-00389-3
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