Sugeno–Weber triangular norm-based aggregation operators under T-spherical fuzzy hypersoft context

Abstract

This research work contributes significantly to the current information field by offering an innovative model named the T-spherical fuzzy hypersoft (T-SFHS) set (T-SFHSS). This framework addresses both aspects of the three-dimensional knowledge implicated in the satisfaction, abstinence, and dissatisfaction inherent in human decision-making. It is an innovative approach to the problem of introducing computer cognition and decision-making in uncertain settings into the real world. The T-SFHSS is superior at determining what to do with unclear or imprecise data. The T-SFHSS enhances fuzzy sets such as the “intuitionistic fuzzy hypersoft set” and the “Pythagorean fuzzy hypersoft set”. It aims to increase the precision of fuzzy set calculations. To aggregate the decision data most effectively, we propose some novel Sugeno-Weber t-norm and t-conorm-based operational rules for T-SFHS numbers (T-SFHSNs). We then propose some T-SFHS aggregation operators with desirable properties in light of these operational laws. We conduct an illustrative study on natural agribusiness to demonstrate the viability and utility of the present methodology. The correctness of the obtained results can be verified by contrasting the proposed SW aggregation operators (AOs) on T-SFSS with the approaches already in use. The findings show that the proposed methodology is more consistent and successful than the current procedures.