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- W2951682600 abstract "The selection of a suitable fi nancing alternative involves multifarious attributes that shouldbe assessed to provide a basis foundation for decision-making. As an effective generation ofintuitionistic fuzzy set and linguistic term, the intuitionistic linguistic set (ILS) has greater power forprocessing uncertain information during decision-making process. Keep this feature in mind, themain purpose of this paper is to investigate a weighted induced aggregation approach for decisionmakingproblem concerning fi nancing selection with complex uncertainty in term of intuitionisticlinguistic (IL) information. For this, a new intuitionistic linguistic aggregation operator based on theweighted induced approach, namely the IL weighted induced ordered average-weighted averaging(ILWIOWAWA) operator, is proposed to integrate intuitionistic linguistic information. The specialadvantage of this operator is that it can integrate the subjective information with the particularattitudinal characters in form of order-induced variables in the same expression during informationfusion. Moreover, it is able to deal with uncertain information represented by intuitionistic linguisticset very effectively. Some of its properties and particular cases are mathematically explored. Wehave proved that it has the properties of monotonicity, boundedness, idempotency, nonnegativityand refl exivity. A further extension of the proposed operator is also represented in term of quasiarithmeticmeans, then we get the quasi-arithmetic ILWIOWAWA (QILWIOWAWA) operator, whichencompasses a very broad class of IL aggregation operators. In addition, based on the developedoperator, a procedure for multiple attribute group decision-making (MAGDM) problems has beendiscussed. Finally, a numerical application related to the discipline evaluation in university is usedto show the validity and practicability of the proposed method." @default.
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- W2951682600 date "2019-06-24" @default.
- W2951682600 modified "2023-10-05" @default.
- W2951682600 title "Financing Selection Method in Discipline Evaluation Using a Weighted Induced Model" @default.
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- W2951682600 doi "https://doi.org/10.15240/tul/001/2019-2-003" @default.
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