On the Interpretability and Representation of Linguistic Fuzzy Systems

A. Riid and E. RĂ¼stern (Estonia)


Fuzzy logic and systems, fuzzy modeling and control, inference algorithm, transparency to interpretation.


Finding the compromise between interpretability, computational complexity and adaptation potential of linguistic fuzzy systems is important in several fields of application particularly in fuzzy modeling and control. This paper considers the role of popular s- and t-norms in fuzzy inference function in this aspect and presents some recently acquired results. First, it is shown that with simultaneous application of product implication and sum aggregation, it is sufficient to consider symmetrical triangular output MFs, which also makes output-side transparency immediately a default property of fuzzy systems. Secondly, analytical inference function for linguistic fuzzy systems utilizing minimum implication is derived for several definitions of output MFs. Finally, some aspects of maximum aggregation are observed. It appears that computational complexity and transparency are somewhat compatible and the compromise is thus attainable as adaptability potential is difficult to realize when inference algorithm becomes too complex because of lack of capable methods and inherent mathematical limitations.

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