<p>Information fusion and information analysis are labor-intensive processes. In information fusion, a set of structural conditions is introduced to reduce uncertainty. Among existing approaches, the Pythagorean fuzzy set (PyFS) method, based on approximate data, provides an effective framework for handling uncertainty when data are obtained under real-world conditions. In addition, flexible and adaptable parametric operators for fuzzy structural conditions include the Aczel–Alsina T-norm (AATN) and the Aczel–Alsina T-conorm (AATC). The main objective of this paper is to present methods for performing basic operations on data represented as Pythagorean fuzzy set values. In this study, operators based on Pythagorean fuzzy sets (PyFS), including the Aczel–Alsina weighted geometric operator (PyFRAAWG), the Aczel–Alsina ordered weighted geometric operator (PyFRAAOWG), and the Aczel–Alsina hybrid weighted geometric operator (PyFAAHWG), are developed based on the Aczel–Alsina T-norm and T-conorm. The key properties of the developed operators are then analyzed and discussed. Furthermore, the proposed approaches are applied to a multi-attribute group decision-making problem. The results are evaluated for different parameter values of the Aczel–Alsina T-norm and T-conorm and are compared with existing methods to assess the effectiveness of the proposed approach. Keywords: Aczel–Alsina T-conorm; Pythagorean fuzzy set; Aczel–Alsina weighted geometric operator; intuitionistic fuzzy set; tonsillitis; multi-attribute decision making; T-norm; T-conorm.</p>