Interpretability of Fuzzy Systems

  • Corrado Mencar
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8256)


Fuzzy systems are convenient tools for modelling complex phenomena because they are capable of conjugating a non-linear behaviour with a transparent description of knowledge in terms of linguistic rules. In many real-world applications, fuzzy systems are designed through data-driven design techniques which, however, often carry out precise systems that are not endowed with knowledge that is interpretable, i.e. easy to read and understand. In a nutshell, interpretability is not granted by the mere adoption of fuzzy logic, this representing a necessary yet not a sufficient requirement for modelling and processing linguistic knowledge. Furthermore, interpretability is a quality that is not easy to define and quantify. Therefore, several open and challenging questions arise while considering interpretability in the design of fuzzy systems, which are briefly considered in this paper along with some answers on the basis of the current state of research.


Fuzzy System Fuzzy Rule Fuzzy Model Linguistic Variable Linguistic Term 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer International Publishing Switzerland 2013

Authors and Affiliations

  • Corrado Mencar
    • 1
  1. 1.University of Bari “A. Moro”Italy

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