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GenSoFNN-Yager: A novel brain-inspired generic self-organizing neuro-fuzzy system realizing Yager inference

Published: 01 November 2008 Publication History

Abstract

Pattern recognition is increasingly becoming a key component of decision support systems (DSSs) in many application areas, especially when automatically extracting semantic rules from data is a chief concern. Accordingly, this paper presents a novel evolving neuro-fuzzy DSS, the generic self-organizing fuzzy neural network realizing Yager inference (GenSoFNN-Yager), that emulates the sequential learning paradigm of the hippocampus in the brain to synthesize from low-level numerical data to high-level declarative fuzzy rules. The proposed system exhibits simple and conceptually firm computational steps that correspond closely to a plausible human logical reasoning and decision-making. Experimental results on sample benchmark problems and realistic medical diagnosis applications show the potential of the proposed system as a competent DSS.

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cover image Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal  Volume 35, Issue 4
November, 2008
628 pages

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Pergamon Press, Inc.

United States

Publication History

Published: 01 November 2008

Author Tags

  1. Decision support system
  2. Declarative knowledge
  3. Hippocampus
  4. Neuro-fuzzy system
  5. Rule induction
  6. Sequential learning
  7. Yager inference scheme

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