Interaction Power Bonferroni Mean Aggregation Operators Based on T-Spherical Fuzzy Information and Their Application in Multi-attribute Decision Making.

T-spherical fuzzy (TSF) set is a suitable technique for depicting uncertain and vague information in real-life problems because it covered the truth, abstinence, falsity, and refusal grade with a suitable characteristic that is the sum of the q-power of the truth, abstinence, and falsity grades will be contained in the unit interval. The major objective of this article is to evaluate the novel theory of interaction operational laws for TSF information. Additionally, power Bonferroni mean (PBM) operators are the combination of two existing ideas such as Bonferroni and power aggregation operator and because of this reason, they are more general than the bundle of existing ideas. Inspired by the above valuable knowledge, we derive the PBM operators based on interaction operation laws for TSF values such as the TSF interaction PBM (TSFIPBM) operator and TSF weighted interaction PBM (TSFWIPBM) operator. Some special cases and the properties of the invented techniques are also examined. Furthermore, for addressing some real-life problems, we derive the multi-attribute decision-making (MADM) method in the consideration of the presented technique to enhance the stability and supremacy of the evaluated techniques. Finally, for comparing the proposed techniques with prevailing methods, we illustrate some numerical examples to show the supremacy and effectiveness of the derived theory. [ABSTRACT FROM AUTHOR]