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Knowledge Acquisition and Processing: New Methods for Neuro-Fuzzy Systems

  • Danuta Rutkowska
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2932)

Abstract

The paper presents some new methods of knowledge acquisition and processing with regard to neuro-fuzzy systems. Various connectionist architectures that reflect fuzzy IF-THEN rules are considered. The so-called flexible neuro-fuzzy systems are described, as well as relational systems and probabilistic neural networks. Other connectionist systems, such hierarchical neuro-fuzzy systems, type 2 systems, and hybrid rough-neuro-fuzzy systems are mentioned. Finally, the perception-based approach, which refers to computing with words and perceptions, is briefly outlined. Within this framework, a multi-stage classification algorithm and a multi-expert classifier are proposed.

Keywords

Membership Function Fuzzy System Knowledge Acquisition Soft Computing Logical Approach 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Danuta Rutkowska
    • 1
    • 2
  1. 1.Department of Computer EngineeringTechnical University of CzestochowaCzestochowaPoland
  2. 2.Department of Artificial IntelligenceWSHE University in LodzLodzPoland

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