Archimedean Aggregation Operators Based on Complex Pythagorean Fuzzy Sets Using Confidence Levels and Their Application in Decision Making

The diagnosed complex Pythagorean fuzzy (CPF) set is a more valuable and dominant tool than the intuitionistic sets to describe awkward unreliable information effectively. Further, Archimedean t-norm t-conorm have significant influence depict relation among aggregated values. To take advantage of CPF t-conorm, assume norms algebraic, Einstein, Hamacher, frank at same time, in this analysis, first, we proposed fundamental operational laws. Second, based on these laws, developed confidence Archimedean-weighted averaging (CCPFSAWA), Archimedean-ordered weighted (CCPFSAOWA), geometric (CCPFSAWG), (CCPFSAOWG) operators implemented their results properties. We know that are general form all-aggregation operators, so by using different values explored CPF-weighted (CCPFWA), CPF-ordered (CCPFOWA), Einstein-weighted (CCPFEWA), Einstein-ordered (CCPFEOWA), Hamacher-weighted (CCPFHWA), Hamacher-ordered (CCPFHOWA), frank-weighted (CCPFFWA), frank-ordered (CCPFFOWA), (CCPFWG), (CCPFOWG), (CCPFEWG), (CCPFEOWG), (CCPFHWG), (CCPFHOWG), (CCPFFWG), (CCPFFOWG) operators. Then, multi-attribute decision-making (MADM) method Finally, many examples used do comparative analysis existing methods show validation new approaches.