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Incremental Update of Fuzzy Rule-Based Classifiers for Dynamic Problems

  • Tomoharu Nakashima
  • Takeshi Sumitani
  • Andrzej Bargiela
Part of the Studies in Computational Intelligence book series (SCI, volume 429)

Abstract

Incremental construction of fuzzy rule-based classifiers is studied in this paper. It is assumed that not all training patterns are given a priori for training classifiers, but are gradually made available over time. It is also assumed the previously available training patterns can not be used in the following time steps. Thus fuzzy rule-based classifiers should be constructed by updating already constructed classifiers using the available training patterns at each time step. Incremental methods are proposed for this type of pattern classification problems. A series of computational experiments are conducted in order to examine the performance of the proposed incremental construction methods of fuzzy rule-based classifiers using a simple artificial pattern classification problem.

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References

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    Lee, C.C.: Fuzzy logic in control systems: Fuzzy logic controller – part I and II. IEEE Transactions on Systems Man and Cybernetics 20(2), 404–435 (1990)zbMATHCrossRefGoogle Scholar
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    Ishibuchi, H., Nakashima, T., Nii, M.: Classification and Modeling with Linguistic Information Granules: Advanced Approaches to Linguistic Data Mining, 1st edn. Springer New York, Inc., Secaucus (2004)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Tomoharu Nakashima
    • 1
  • Takeshi Sumitani
    • 1
  • Andrzej Bargiela
    • 2
  1. 1.Graduate School of EngineeringOsaka Prefecture UniversitySakaiJapan
  2. 2.University of NottinghamNottinghamU.K.

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