Abstract
In the present paper, we introduce a new parametric fuzzy divergence measure on intuitionistic fuzzy sets. Some properties of the proposed measure are also being studied. In addition, the application of the intuitionistic fuzzy divergence measure in decision making and consequently choosing the best medicines and treatment for the patients has also been discussed. There are some diseases for which vaccine is not available. In that case, we have devised a method to choose the best treatment for the patients based on the results of clinical trials.
Highlights
Pn) After that, various other generalized measures of entropy were developed taking Shannon’s entropy as the base
Atanassov [14] proposed the concept of intuitionistic fuzzy set (IFS) which has broadened the idea of fuzzy set with the addition of degree of non-membership
As IFS theory is more efficient in taking care of the uncertainties in information, it is much better than the crisp set theory
Summary
Corresponding to De Luca and Termini’s fuzzy entropy measure [16], Vlachos and Sergiadis [17] extended their measure in the IFS environment. Verma and Sharma [23] improvised the divergence measure of Wei and Ye. Harish Garg et al [24] proposed parametric version of intuitionistic fuzzy divergence measure given by Verma and Sharma [23]. Srivastava [25] pointed that that the measures given by Vlachos and Sergiadis [17], Zhang and Jiang [21], Junjun et al [18] do not satisfy the basic requirement of nonnegativity of the intuitionistic fuzzy divergence measure. Ohlan [26] extended the idea of Fan and Xie [27] and proposed an intuitionistic fuzzy exponential divergence measure. Afterwards, we examine its properties and provide an illustration of how it can help in choosing the best medical treatment for the patients
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