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Fuzzy rule clustering

Authors: Paulo Salgado;

Fuzzy rule clustering

Abstract

The concept of relevance has been proposed as a measure of the relative importance of sets of rules, allowing the development of a new methodology for organising the linguistic information: SLIM (Separation of Linguistic Information Methodology). Based on this concept and on this methodology, a new fuzzy clustering of fuzzy rules algorithm (FCFRA) is proposed and applied to organise fuzzy IF ... THEN rules. The proposed FCFRA algorithm has been successfully applied to illustrate a segmentation operation in the "fuzzy rules domain", using the Abington Cross image.

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Powered by OpenAIRE graph
Found an issue? Give us feedback
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!
2
Average
Average
Average
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