Analyzing the Sustainability of Industry Affected in COVID-19 Pandemic Scenario Using Cosine Similarity Measure under SVPNS and PNN Model

Authors

Priyanka Majumder
Florentin Smarandache, University of New MexicoFollow

Document Type

Article

Publication Date

2022

Abstract

COVID-19 outbreak is a reminder of the fact that the pandemics have happened in the past and will also occur in the future. The COVID-19 not only has affected the economy; but also it has affected the livelihood, which leads to the changes in businesses. This study aims to identify the most significant indicator (or parameter) that impacts the sustainability of industries. The study should also develop a realtime monitoring system for the sustainability of industries affected by COVID 19. In this work, the Polynomial Neural Network (PNN) and cosine similarity measure under SVPNS (Single-Valued Pentapartitioned Neutrosophic Set) environment have found their use in analyzing the sustainability of the industry.

Publication Title

International Journal of Neutrosophic Science

Language (ISO)

English

Keywords

COVID-19; SVPNS; cosine similarity measure; Polynomial Neural Network; sustainability.

Recommended Citation

Majumder, Priyanka and Florentin Smarandache. "Analyzing the Sustainability of Industry Affected in COVID-19 Pandemic Scenario Using Cosine Similarity Measure under SVPNS and PNN Model." International Journal of Neutrosophic Science (2022). https://digitalrepository.unm.edu/math_fsp/589

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.