An intelligent fuzzy parameterized MADM-approach to optimal selection of electronic appliances based on neutrosophic hypersoft expert set

Abstract

When compared to its extension, the hypersoft set, which deals with discontinuous attribute-valued
sets corresponding to different attributes, the soft set only works with a single set of attributes. Numerous
scholars created models based on soft sets to address issues in a variety of domains, including decision-making
and medical diagnostics. However, these models only take into account one expert, which causes numerous
issues for users, particularly when creating questions. We provide a fuzzy parameterized neutrosophic hypersoft
expert set to eliminate this mismatch. In addition to addressing the issue of dealing with a single expert, this
approach also addresses the problem of soft sets not being adequate for discontinuous attribute-valued sets
corresponding to different attributes. The notion of fuzzy parameterized neutrosophic hypersoft expert sets,
which combines fuzzy parameterized neutrosophic sets and hypersoft expert sets, is first introduced in this work.
Examples are provided to help illustrate some key fundamental concepts, aggregation operations and results.
A decision-making application is shown at the end to demonstrate the viability of the suggested theory