Similarity measure-based three-way decisions in Pythagorean fuzzy information systems and its application in FANETs

The existing researchers generalize the decision-theoretic rough sets (DTRSs) model from the viewpoint of the cost function, whether the information system is complete, and so on. Few of them consider multiple different strategies to rank the expected losses. Furthermore, under the circumstance of Pythagorean fuzzy, we can't directly define the partition of the objects set by employing equivalence relation, there is a need for constructing the general binary relation. Aiming at these problems, in present paper, we propose the similarity measure-based three-way decisions (3WD) in Pythagorean fuzzy information systems, both the binary relation and the similarity neighborhood are induced by similarity measure between objects. Each object has its own losses, different strategies are designed to rank the expected losses. Further, the similarity measure-based DTRSs dealing with crisp concept and the similarity measure-based Pythagorean fuzzy DTRSs dealing with Pythagorean fuzzy concept are developed to establish the three regions of similarity measure-based 3WD. Finally, the proposed models are used to make decisions for classifying the network nodes of flying ad-hoc networks (FANETs) into normal nodes also called safe nodes, suspicious nodes, and malicious nodes also called unsafe nodes under the evaluation of Pythagorean fuzzy information.