Abstract
In the definition of the complex neutrosophic soft expert set (CNSES), parameters set is a classical set, and the parameters have the same degree of importance, which is considered as 1. This poses a limitation in modeling of some problems. This paper introduces the concept of fuzzy parameterized complex neutrosophic soft expert set (FP-CNSES) to handle this issue by assigning a degree of importance to each of the problem parameters. We further develop FP-CNSES by establishing the concept of weighted fuzzy parameterized complex neutrosophic soft expert set (WFP-CNSES) based on the idea that each expert has a relative weight. These new mathematical frameworks reduce the chance of unfairness in the decision making process. Some essential operations with their properties and relevant laws related to the notion of FP-CNSES are defined and verified. The notation of mapping on fuzzy parameterized complex neutrosophic soft expert classes is defined and some properties of fuzzy parameterized complex neutrosophic soft expert images and inverse images was investigated. FP-CNSES is used to put forth an algorithm on decision-making by converting it from complex state to real state and subsequently provided the detailed decision steps. Then, we provide the comparison of FP-CNSES to the current methods to show the ascendancy of our proposed method.
Highlights
In a world where not everything is certain, the need to represent uncertain data was successfully fulfilled by Zadeh [1] by introducing the concept of fuzzy sets
Soft set was extended to the soft expert set [7], which was further developed to fuzzy soft expert set (FSES) [8], intuitionistic fuzzy soft expert sets (IFSES) [9] and single valued neutrosophic soft expert sets (SVNSES) [10]
We extend the studies on complex neutrosophic soft expert set (CNSES) [23] and FP-SVNSES [18] through the establishment of the notion of FP-CNSES to keep the advantages of CNSES
Summary
In a world where not everything is certain, the need to represent uncertain data was successfully fulfilled by Zadeh [1] by introducing the concept of fuzzy sets. These sets can only handle incomplete and uncertainty information but not indeterminate and inconsistent information, which usually exists in real situations To treat this deficiency, Al-Quran and Hassan [18] defined the fuzzy parameterized single valued neutrosophic soft expert set (FP-SVNSES), which proves superior to these models with three independent membership functions. Indeterminate, inconsistent, and incomplete information that has periodic nature, Ali and Smarandache [22] introduced complex neutrosophic set, where each membership function associates with a phase term This feature gives wave-like properties that could be used to describe constructive and destructive interference depending on the phase value of an element, as well as its ability to deal with indeterminacy.
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