Some novel q‐rung orthopair fuzzy similarity measures and entropy measures with their applications

Abstract

In this paper, we have introduced some new similarity measures for q-rung orthopair fuzzy sets and discussed their various features. These similarity measures have been constructed with the help of t-conorms. The suggested similarity measures are more effective than the available ones in computing the similarity between distinct q-rung orthopair fuzzy sets. With the help of these suggested similarity measures, we have also developed some novel entropy measures for q-rung orthopair fuzzy sets. The newly proposed entropy measures are more effective than the existing ones in handling linguistic hedges. The applicability of the suggested similarity measures has been demonstrated in pattern analysis and the findings have been found to be better than due to existing ones. The traditional decision-making method namely, the technique for order preference by similarity to the ideal solution gives us a compromise solution that is either closest to the positive ideal solution and farthest from the negative ideal solution but not both. So, to overcome this major drawback, we suggest a novel multi-attribute decisionmaking method in the q-rung orthopair fuzzy environment and apply it to a decisionmaking problem.