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1.
Cognitive Intelligence with Neutrosophic Statistics in Bioinformatics ; : 393-415, 2023.
Article in English | Scopus | ID: covidwho-2292009

ABSTRACT

The research for treatments and vaccines for novel coronavirus disease (COVID-19) is still going on. Desperation in the community, particularly among middle- and low-income groups who have been hit hard by the economic effects of forced lockdowns, has sparked a surge in interest in alternative medical plant-based therapies. This article attempts to provide evidence summaries examining the potential of complementary therapies in COVID-19 management by studying the findings of some wild medicinal edible plants that have been reported to have antiviral, anti-inflammatory, and immunomodulatory activities. We examine and compare the current growth pattern of COVID-19 between tribal and non-tribal people in different regions of Kokrajhar, Assam, India, where during the COVID-19 pandemic tribes have increased their use of wild medicinal edible herbs, and the recovery rate of COVID-19 is high in comparison to non-tribal people of the same area to describe the current state of wild medicinal edible plant use and provide critical recommendations to the relevant authorities. In addition, this study presents a multi-criteria decision-making procedure based on the neutrosophic VIKOR method to survey the region where most wild medicinal edible plants are used and found. Also, with the help of the neutrosophic VIKOR method, we can identify the regions where most people of the Kokrajhar district are affected and recovered. © 2023 Elsevier Inc. All rights reserved.

2.
Journal of Intelligent and Fuzzy Systems ; 43(4):4555-4564, 2022.
Article in English | Scopus | ID: covidwho-2022590

ABSTRACT

These days, the appraisal of the COVID-19 vulnerability has become a difficult errand for the whole world. The COVID-19 administration dynamic issue frequently includes numerous elective arrangements clashing standards. In this paper, we present a multi-criteria decision-making (MCDM) procedure based on the fuzzy VIKOR method to survey the COVID-19 vulnerability in the state of Assam, India. The trapezoidal fuzzy number is utilized to evaluate the rating of the loads for the set-up models. We have observed environment, social, and Medical factors after observing the spread of COVID-19. To study and to have comments, a committee of five experts has been formed from a different region of Assam to observe and comment to identify Coronavirus's weakest factors. For a better survey, we have divided the state into four areas namely Rural Area, Urban Area, Market Area in Rural Area, and Market Area in Urban Area. The current research looked at how the fuzzy VIKOR selects provinces for urgent adaptation needs differently than a traditional MCDM technique. © 2022 - IOS Press. All rights reserved.

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