Novel distance measures for cubic intuitionistic fuzzy sets and their applications to pattern recognitions and medical diagnosis

Cubic intuitionistic fuzzy set (IFS), handles the uncertainties by characterizing them into membership and non-membership interval in form of interval-valued IFS and further the degree of agreement, as well as disagreement corresponding to these intervals, is given in the form of an IFS. Under this environment, some series of distance measures based on Hamming, Euclidean, and Hausdorff metrics are proposed. Various relations among them are derived. The practical relevance of our work is justified by giving two real-life examples, one on medical diagnosis and other on pattern recognition. Further, comparison analysis has been done with the existing decision-making approaches and the advantages of the proposed approach are highlighted.