Psychology of Women And Men in Quitting Tobacco Usage Using Madm as an Application of Intuitionistic Fuzzy Set

Abstract

MADM (Multi – Attribute Decision Making) is one of the most popular research topics in the subject of group decision making and Data Science. MADM problem of alternatives under different attributes is given in the form of intuitionistic number (IFN), intuitionistic fuzzy set (IFS), which plays a vital role in dealing with uncertain and incomplete information. The modified similarity measures of IFSs based on cosine similarity, develop a MADM method. Distance measure and similarity measure are the important content of IFS. Euclidean distance is applied by taking the hesitation degree into account. In addition to the distance measure the modified Euclidean similarity measure has received attention. Hung and Wang (2012) considered the membership degree, non-membership degree and hesitation degree and then defined a modified cosine similarity for IFS. In this paper membership degree, non-membership degree and hesitation degree of IFS based on the modified Euclidean similarity measure E_M(A,B) for two IFSs,                                                   A = ( )  and B =( ) is expressed as follows

and  modified  Canberra distance expressed as follows:

Decision making skill in quieting tobacco usage is found using MADM as an Application of Intuitionistic Fuzzy Set (IFS) with the attribute’s women and men and arrived same conclusion using two different similarity measure.