On Novel Hellinger Divergence Measure of Neutrosophic Hypersoft Sets in Symptomatic Detection of COVID-19

Abstract

Numerous decision science processes involves the divergence measure is the most suitable
information measure for dealing with the vagueness and impreciseness of the factors affecting the
decision-making models. In this manuscript, a new kind of Hellinger information measure for a
single-valued neutrosophic hypersoft set along with some important results have been presented
and studied in detail. Also, we have presented the implementation of the proposed information
measure to deal with the symptomatic detection of COVID-19 with a numerical illustration. In view
of the existing methods related to divergence measures, some comparative results and remarks
along with some important advantages have also been presented.