Publication | Closed Access
Designing Fuzzy Sets With the Use of the Parametric Principle of Justifiable Granularity
107
Citations
21
References
2015
Year
Introduced MethodFuzzy LogicMembership FunctionsEngineeringData ScienceData MiningUncertainty QuantificationFuzzy ComputingInformation GranuleFuzzy ModelingFuzzy MathematicsFuzzy SetsJustifiable GranularityIntelligent SystemsDiscrete MathematicsRough SetParametric PrincipleFuzzy Pattern Recognition
This study is concerned with a design of membership functions of fuzzy sets. The membership functions are formed in such a way that they are experimentally justifiable and exhibit a sound semantics. These two requirements are articulated through the principle of justifiable granularity. The parametric version of the principle is discussed in detail. We show linkages with type-2 fuzzy sets, which are constructed on a basis of type-1 fuzzy sets. Several experimental studies are reported, which illustrate a behavior of the introduced method.
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