Abstract
This year, various researchers paid the attention towards the analysis of m-polar fuzzy attributes for knowledge-processing tasks. In this process, a problem addressed while dealing with acceptation, rejection and uncertain parts of m-polar fuzzy attributes. One of suitable example is classifying the potential researchers of the given field to upscale the university ranking is a major issue for the academic or research team as it is based on multi-valued parameters. This becomes more complex when several random, ghost or fake researchers exist in the university. These types of researchers used to have several papers in most of the research areas rather than a specialized field. Hence, it is difficult for any expert to characterize them based on their truth, false or indeterminant areas based on the given n-number of papers to upscale the university ranking. To solve this problem, two methods are proposed in this paper using the algebra of n-valued neutrosophic set and its Euclidean distance with an illustrative example.
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