Neural networks and genetic algorithm approaches to auto-design of fuzzy systems

  • Hideyuki Takagi
  • Michael Lee
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 695)


This paper presents Neural Network and Genetic Algorithm approaches to fuzzy system design, which aims to shorten development time and increase system performance. An approach that uses neural network to represent multi-dimensional nonlinear membership functions and an approach to tune membership function parameters are given. A genetic algorithm approach that integrates and automates three fuzzy system design stages is also proposed.


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Copyright information

© Springer-Verlag Berlin Heidelberg 1993

Authors and Affiliations

  • Hideyuki Takagi
    • 1
  • Michael Lee
    • 1
  1. 1.Computer Science DivisionUniversity of CaliforniaBerkeley

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