Measuring and aggregating ε-T-transitive fuzzy relations

Abstract

The transitivity of fuzzy relations plays an important role in fuzzy set theory, artificial intelligence, clustering and decision-making. However, it is often difficult for fuzzy relations to satisfy the transitivity property in many practical applications. This has motivated researchers to investigate the degree to which a fuzzy relation is transitive. Therefore, this work first investigates two different measures of T-transitivity for fuzzy relations using some well-known fuzzy implications. And then, the relationship between two different degrees of transitivity is investigated. Further, the concept of an ε-T-transitive fuzzy relation is introduced, and the aggregation functions that preserve the ε-T-transitivity of fuzzy relations are characterized. Finally, the ε-T-transitive fuzzy relation is utilized to make inferences and cluster objects. Compared to finding the T-transitive closure, it is reasonable to cluster objects using the ε-T-transitive fuzzy relation under the permissible error.