Gradient Descent Based Optimization of Transparent Mamdani Systems

  • Andri Riid
  • Ennu Rüstern
Conference paper
Part of the Advances in Soft Computing book series (AINSC, volume 19)


The tradeoff between accuracy and interpretability in fuzzy modeling has shifted into focus in last few years. This paper aims at improving accuracy of linguistic models while maintaining a good interpretability. A new gradient-based method, extended version of Jager approach, is proposed for the optimization of transparent Mamdani systems. The advantage of Mamdani systems if compared to 0th order TS systems in Jager approach is that their interpolation properties allow one to obtain less complex models without loss of accuracy. Several modeling examples confirming the advantages of the chosen algorithm are included.


Membership Function Fuzzy System Gradient Descent Interpolation Property Linguistic Label 
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-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Andri Riid
    • 1
  • Ennu Rüstern
    • 1
  1. 1.Department of Computer ControlTallinn Technical UniversityTallinnEstonia

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