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2002

COR: a methodology to improve ad hoc data-driven linguistic rule learning methods by inducing cooperation among rules

13 years 5 months ago
COR: a methodology to improve ad hoc data-driven linguistic rule learning methods by inducing cooperation among rules
This paper introduces a new learning methodology to quickly generate accurate and simple linguistic fuzzy models, the cooperative rules (COR) methodology. It acts on the consequents of the fuzzy rules to find those best cooperating. Instead of selecting the consequent with the highest performance in each fuzzy input subspace as ad hoc data-driven methods usually do, the COR methodology considers the possibility of using another consequent, different from the best one, when it allows the fuzzy model to be more accurate thanks to having a rule set with best cooperation. Our proposal has shown good results solving three different applications when compared to other methods.
Jorge Casillas, Oscar Cordón, Francisco Her
Added 23 Dec 2010
Updated 23 Dec 2010
Type Journal
Year 2002
Where TSMC
Authors Jorge Casillas, Oscar Cordón, Francisco Herrera
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