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Interpretability and learning in neuro-fuzzy systems

descriptionPublicationkeyboard_double_arrow_right Article 01 Oct 2004 Portugal English Publisher:Elsevier BVJournal:Fuzzy Sets and Systems, volume 147, pages 17-38 (issn: 0165-0114, Copyright policy )
Authors: Rui Pedro Paiva; António Dourado;

doi: 10.1016/j.fss.2003.11.012

handle: 10316/4103

Interpretability and learning in neuro-fuzzy systems

Abstract

zbMATH Open Web Interface contents unavailable due to conflicting licenses.

Country
Portugal
Related Organizations
Keywords

Neuro-fuzzy systems, Learning and adaptive systems in artificial intelligence, Interpretability, System identification, Transparency, Fuzzy system models, Clustering

  • BIP!
    Impact byBIP!
    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    		 94
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    		 Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    		 Top 1%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    		 Top 10%
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
94
Top 10%
Top 1%
Top 10%
Green
bronze