Intuitionistic fuzzy-valued neutrosophic multi-sets and numerical applications to classification

Abstract A single-valued neutrosophic multi-set is characterized by a sequence of truth membership degrees, indeterminacy degrees and falsity degrees. Nature allows us to consider multiple information in the truth, memberships which pretty useful multi-criteria group decision making. In this paper, we sequences intuitionistic fuzzy values instead numbers define concept fuzzy-valued multi-set. manner, such set gives more powerful information. We also present some theoretic operations partial order for sets provide algebraic between values. Then, develop two types weighted aggregation operators with help t -norms -conorms. By considering well-known additive generators ordinary -norms, give Algebraic arithmetic geometric Einstein that are particular cases defined via general simplified valued similarity measure use score function rank similarities multi-values. Finally, an algorithm solve classification problems using multi-values proposed apply theoretical part paper real problem.