Multi-criteria decision making based on novel distance measure in intuitionistic fuzzy environment

In comparison to fuzzy sets, intuitionistic sets are much more efficient at representing and processing uncertainty. Distance measures quantify how the information conveyed by differs from one another. Researchers have suggested many distance assess difference between but several of them produce contradictory results in practice violate fundamental axioms measure. this article, we introduce a novel measure for IFSs, visualize it, discuss its boundedness nonlinear characteristics using appropriate numerical examples. addition establishing validity, effectiveness was investigated real-life examples multiple fields, such as medical diagnosis pattern recognition. We also present technique solve recognition problems, superiority proposed approach over existing approaches is demonstrated incorporating performance index terms "Degree Confidence" (DOC). Finally, extend applicability establish new decision-making known IFIR (Intuitionistic Fuzzy Inferior Ratio) method, efficiency analyzed with other established approaches.