A Cluster Analysis Approach for Rule Base Reduction View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2019

AUTHORS

Luca Anzilli , Silvio Giove

ABSTRACT

In this paper we propose an iterative algorithm for fuzzy rule base simplification based on cluster analysis. The proposed approach uses a dissimilarity measure that allows to assign different importance to values and ambiguities of fuzzy terms in antecedent and consequent parts of fuzzy rules.

PAGES

307-318

References to SciGraph publications

  • 2007. A Bounded Index for Cluster Validity in MACHINE LEARNING AND DATA MINING IN PATTERN RECOGNITION
  • Book

    TITLE

    Neural Advances in Processing Nonlinear Dynamic Signals

    ISBN

    978-3-319-95097-6
    978-3-319-95098-3

    Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1007/978-3-319-95098-3_28

    DOI

    http://dx.doi.org/10.1007/978-3-319-95098-3_28

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1105760342


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