Journal article Open Access
Abhishek Guleria; Saurabh Srivastava; Rakesh Kumar Bajaj
In various decision-making models the divergence measure is found to be a useful information measure in handling impreciseness and uncertainty among the qualitative and quantitative factors of the decision-making process. In the proposed work, a novel parametric divergence measure for neutrosophic sets has been proposed along with its various properties. On the basis of the proposed parametric divergence measure, we have outlined some methodologies along with its implementing procedural steps for classification problem (pattern recognition problem, medical diagnosis problem) and multi criteria decision making problem. Also, numerical examples for the application problems have been provided for illustration of the proposed methodologies. Comparative remarks along with necessary observations and advantages have also been presented in view of the existing appraoches.