Encyclopedia of Complexity and Systems Science

2009 Edition
| Editors: Robert A. Meyers (Editor-in-Chief)

Evolving Fuzzy Systems

  • Plamen Angelov
Reference work entry
DOI: https://doi.org/10.1007/978-0-387-30440-3_192

Definition of the Subject

Evolving Fuzzy Systems (EFS) are a class of Fuzzy Rule‐based (FRB) andNeuro‐Fuzzy (NF) systems that have both their parameters and underlying structure self‐adapting, self‐developing, self‐learningfrom the data in on‐line mode and, possibly, in real‐time. The concept was conceived at the beginning of this century [2,5]. Parallel investigations have led to similar developments inneural networks (NN) [41,42]. EFS have thesignificant advantage compared to the evolving NN of being linguistically tractable and transparent. EFS have been instrumental in the emergence of newbranches of evolving clustering algorithms [3], evolving classifiers [16,51], evolving time‐seriespredictors  [9,47], evolving fuzzy controllers [4], evolving fault detectors  [30] etc. Over the last years EFS has demonstrated a wide range of applications spanningrobotics [76] and defense [24] tobiomedical [70] and industrial process [29]data processing in real‐time, new generations of...

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The author would like to thank Mr. Xiaowei Zhou for his assistance in producing the illustrative material, Dr. Jose Macias Hernandez forkindly providing real data from the oil refinery CEPSA, Santa Cruz, Tenerife, Spain, Dr. Richard Buswell, Loughborough University and ASHRAE(RP‐1020) for the real air conditioning data, and Dr. Edwin Lughofer from Johannes Kepler University of Linz, Austria for providing real data fromcar engines.


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Copyright information

© Springer-Verlag 2009

Authors and Affiliations

  • Plamen Angelov
    • 1
  1. 1.Intelligent Systems Research Laboratory, Digital Signal Processing Research Group, Communication Systems DepartmentLancaster UniversityLancasterUK