AHP-Based Aczel–Alsina Prioritization under T-Spherical Fuzzy Information for Artificial Intelligence in Smart Systems

This paper presents a novel total prioritized aggregation framework based on the AHP-driven Aczel–Alsina t-norm (AA-TN) and Aczel–Alsina t-conorm (AA-TCN) within the context of T-spherical fuzzy sets (T-SFSs) to address uncertainty in complex decision-making problems. The T-SFS framework provides a flexible and effective environment for representing uncertain information. Furthermore, the AA-TN and AA-TCN offer adaptable operational mechanisms through the parameter , while prioritized aggregation enables the efficient incorporation of the relative importance of attributes. To integrate these concepts, two novel aggregation models, namely the T-spherical fuzzy Aczel–Alsina averaging (T-SFAAA) and T-spherical fuzzy Aczel–Alsina geometric (T-SFAAG) approaches, are developed. In addition, the analytical hierarchy process (AHP) is employed to determine the priority weights of criteria in multi-attribute decision-making (MADM) problems.