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- W4281645726 abstract "Purpose The main purpose of this article is to characterize a novel neutrosophic hypersoft set hybrid called possibility single-valued neutrosophic hypersoft set (psv-NHSS) for evaluation of investment projects by using its aggregation operations and decision-support system. Design/methodology/approach Two approaches are employed in this article: set-theoretic approach and algorithmic approach. The former one is used to characterize the novel notion of psv-NHSS and its aggregations. The later one is used to construct a decision-support system by using the aggregations like core matrix, maximum-valued decision, minimum-valued decision and scoring-valued decision of psv-NHSS. The adopted algorithm is implemented in real-world scenario of hydroelectric power station project evaluation for investment purpose. Findings The proposed model is more flexible and reliable as it addresses the limitations of literature on neutrosophic set, neutrosophic soft set and other fuzzy set-like models by considering possibility degree, hypersoft setting and neutrosophic setting collectively. Research limitations/implications It has limitations for decision-making situations where selection of parameters is of uncertain nature. Practical implications The scope of this study may cover a wide range of applications in many fields of mathematical sciences like artificial intelligence, optimization, multiple-criteria decision-making (MCDM), theoretical computer science, soft computing, mathematical statistics, etc. Originality/value The proposed model bears the characteristics of most of the relevant existing models collectively and fulfills their insufficiencies by introducing a novel approximate mapping." @default.
- W4281645726 created "2022-06-13" @default.
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- W4281645726 date "2022-05-31" @default.
- W4281645726 modified "2023-10-03" @default.
- W4281645726 title "An intelligent multiple-criteria decision-making approach based on sv-neutrosophic hypersoft set with possibility degree setting for investment selection" @default.
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- W4281645726 doi "https://doi.org/10.1108/md-04-2022-0462" @default.
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