Restoring consistency in systems of fuzzy gradual rules using similarity relations

Abstract

We present here a method that uses similarity relations to restore consistency in fuzzy gradual rules systems: we propose to transform potentially inconsistent rules by making their consequents more imprecise. Using a suitable similarity relation we obtain consistent rules with a minimum of extra imprecision. We also present an application to illustrate the approach.