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Design of Interval Type-2 Fuzzy Relation-Based Neuro-Fuzzy Networks for Nonlinear Process

  • Dong-Yoon Lee
  • Keon-Jun Park
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 339)

Abstract

In this paper, we introduce the design of interval type-2 fuzzy relation-based neuro-fuzzy networks (IT2FRNFN) for modeling nonlinear process. IT2FRNFN is the network of combination between the neuro-fuzzy network (NFN) and interval type-2 fuzzy set with uncertainty. The premise part of the network is composed of the fuzzy relation division of input space and the consequence part of the network is represented by polynomial functions with interval set. And we also consider genetic algorithms to determine the structure and estimate the values of the parameters. The proposed network is evaluated with the nonlinear process.

Keywords

Neuro-Fuzzy Networks (NFN) Interval Type-2 Fuzzy Set (IT2FS) Genetic Algorithms (GAs) Nonlinear process Modeling 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Dong-Yoon Lee
    • 1
  • Keon-Jun Park
    • 2
  1. 1.Department of Electrical Electronic EngineeringJoongbu UniversityGeumsan-gunSouth Korea
  2. 2.Department of Electrical Information and Communication EngineeringWonkwang UniversityIksan-siSouth Korea

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