Entropy and similarity measures of q-rung orthopair fuzzy soft sets and their applications in decision making problems

The q-rung orthopair fuzzy set can represent a wide range of uncertainty in information. When combined with a soft set, the resulting notion of a q-rung orthopair fuzzy soft set (OFSSq ) is more effective in dealing with uncertainties as it allows for parameterization. The OFSSq is a parameterized family of q-rung orthopair fuzzy sets and a generalization of the Intuitionistic fuzzy soft set (IFSS), the Pythagorean fuzzy soft set (PFSS) and the Fermatean fuzzy soft set (FFSS). While entropy and similarity measures have been defined for these fuzzy set extensions, defining these measures for OFSSq provides generalized expressions that apply to all these special cases. This article proposes distinct expressions for entropy and similarity measures for OFSSq s. The proposed entropy measure aids in assessing uncertainty within an OFSSq , while the similarity measure identifies the degree of similarity between any two OFSSqs. This article showcases the use of the suggested entropy and similarity measures in decision making, highlighting their effectiveness. Both concepts of entropy and similarity will be applied to decision making problems related to Covid-19 pandemic, especially when some dubious inputs are present, and a quick decision must be made.