IEEE Transactions on Fuzzy Systems· 2015Q1
Designing Fuzzy Sets With the Use of the Parametric Principle of Justifiable Granularity
- 108citations
- Q1SCImago
- 2015year
Short summary
A new parametric method designs fuzzy set membership functions that are experimentally justifiable and semantically sound, based on the principle of justifiable granularity.
AI-generated from the title and abstract; the full text is not read.
Key points
- Introduces a parametric version of the justifiable granularity principle for fuzzy set design.
- Membership functions are designed to be experimentally justifiable and semantically sound.
- Demonstrates linkages between the proposed method and type-2 fuzzy sets.
- Experimental studies validate the behavior and utility of the introduced method.
AI-generated from the title and abstract; the full text is not read.
Abstract
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.
The authors' abstract, as published at the source. IEEE Transactions on Fuzzy Systems, 2015 · DOI ↗
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Field: Discrete Mathematics and Combinatorics
Discrete Mathematics and CombinatoricsMathematics