A New Hybrid Fuzzy Aggregation Approach

Abstract

Fuzzy graph theory is useful in the analysis of systems with uncertainty, ambiguity and imprecision. Classical fuzzy graph models usually rely on simple aggregation operators that may not be sufficient to describe complex interactions in uncertain situations. We propose a novel Hybrid Sugeno-Dombi operator by combining the Sugeno intrinsic with Dombi t-norm in this paper. The proposed hybrid framework integrates the Sugeno integral for global information aggregation with the Dombi t-norm for local edge evaluation, thus providing enhanced versatility and flexibility for uncertainty modelling. The suggested approach enhances the efficiency of decision-making and system modeling in complicated real-world applications and delivers a consistent and efficient framework for the analysis of uncertain network systems.