Induced Choquet Integral Aggregation Operators with Single-Valued Neutrosophic Uncertain Linguistic Numbers and Their Application in Multiple Attribute Group Decision-Making

aggregation operators is unsuitable. Thus, applying Choquet integral operator to approximate and simulate human subjective

decision-making process, in which independence among the input arguments is not necessarily assumed, would be suitable.

Moreover, using single-valued neutrosophic uncertain linguistic sets (SVNULSs) can express the indeterminate, inconsistent,

and incomplete information better than FSs and IFSs. In this paper, we studied the MAGDM problems with SVNULSs and

proposed two single-valued neutrosophic uncertain linguistic Choquet integrate aggregation operators where the interactions

phenomena among the attributes or the experts are considered. First, the definition, operational rules, and comparison method

of single-valued neutrosophic uncertain linguistic numbers (SVNULNs) are introduced briefly. Second, induced single-valued

neutrosophic uncertain linguistic Choquet ordered averaging (I-SVNULCA) operator and induced single-valued neutrosophic

uncertain linguistic Choquet geometric (I-SVNULCG) operator are presented. Moreover, a few of its properties are discussed.

Further, the procedure and algorithm of MAGDM based on the above single-valued neutrosophic uncertain linguistic Choquet

integral operator are proposed. Finally, in the illustrative example, the practicality and effectiveness of the proposed method would be demonstrated.