Cargando…
Mediative fuzzy logic mathematical model: A contradictory management prediction in COVID-19 pandemic
This paper presents a model based on mediative fuzzy logic in this COVID-19 pandemic. COVID-19 (novel coronavirus respiratory disease) has become a pandemic now and the whole world has been affected by this disease. Different methodologies and many prediction techniques based on various models have...
Autores principales: | , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier B.V.
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7942162/ https://www.ncbi.nlm.nih.gov/pubmed/33723486 http://dx.doi.org/10.1016/j.asoc.2021.107285 |
_version_ | 1783662266021838848 |
---|---|
author | Sharma, M.K. Dhiman, Nitesh Vandana Mishra, Vishnu Narayan |
author_facet | Sharma, M.K. Dhiman, Nitesh Vandana Mishra, Vishnu Narayan |
author_sort | Sharma, M.K. |
collection | PubMed |
description | This paper presents a model based on mediative fuzzy logic in this COVID-19 pandemic. COVID-19 (novel coronavirus respiratory disease) has become a pandemic now and the whole world has been affected by this disease. Different methodologies and many prediction techniques based on various models have been developed so far. In the present article, we have developed a mediative fuzzy correlation technique based on the parameters for COVID-19 patients from different parts of India. The proposed mediative fuzzy correlation technique provides the relation between the increments of COVID-19 positive patients in terms of the passage of increment with respect to time. The peaks of infected cases in connection with the other condition are estimated from the available data. The mediative fuzzy logic mathematical model can be utilized to find a good fit or a contradictory model for any pandemic model. The proposed approach to the prediction in COVID-19 based on mediative fuzzy logic has produced promising results for the continuous contradictory prediction in India. |
format | Online Article Text |
id | pubmed-7942162 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Elsevier B.V. |
record_format | MEDLINE/PubMed |
spelling | pubmed-79421622021-03-11 Mediative fuzzy logic mathematical model: A contradictory management prediction in COVID-19 pandemic Sharma, M.K. Dhiman, Nitesh Vandana Mishra, Vishnu Narayan Appl Soft Comput Article This paper presents a model based on mediative fuzzy logic in this COVID-19 pandemic. COVID-19 (novel coronavirus respiratory disease) has become a pandemic now and the whole world has been affected by this disease. Different methodologies and many prediction techniques based on various models have been developed so far. In the present article, we have developed a mediative fuzzy correlation technique based on the parameters for COVID-19 patients from different parts of India. The proposed mediative fuzzy correlation technique provides the relation between the increments of COVID-19 positive patients in terms of the passage of increment with respect to time. The peaks of infected cases in connection with the other condition are estimated from the available data. The mediative fuzzy logic mathematical model can be utilized to find a good fit or a contradictory model for any pandemic model. The proposed approach to the prediction in COVID-19 based on mediative fuzzy logic has produced promising results for the continuous contradictory prediction in India. Elsevier B.V. 2021-07 2021-03-09 /pmc/articles/PMC7942162/ /pubmed/33723486 http://dx.doi.org/10.1016/j.asoc.2021.107285 Text en © 2021 Elsevier B.V. All rights reserved. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. |
spellingShingle | Article Sharma, M.K. Dhiman, Nitesh Vandana Mishra, Vishnu Narayan Mediative fuzzy logic mathematical model: A contradictory management prediction in COVID-19 pandemic |
title | Mediative fuzzy logic mathematical model: A contradictory management prediction in COVID-19 pandemic |
title_full | Mediative fuzzy logic mathematical model: A contradictory management prediction in COVID-19 pandemic |
title_fullStr | Mediative fuzzy logic mathematical model: A contradictory management prediction in COVID-19 pandemic |
title_full_unstemmed | Mediative fuzzy logic mathematical model: A contradictory management prediction in COVID-19 pandemic |
title_short | Mediative fuzzy logic mathematical model: A contradictory management prediction in COVID-19 pandemic |
title_sort | mediative fuzzy logic mathematical model: a contradictory management prediction in covid-19 pandemic |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7942162/ https://www.ncbi.nlm.nih.gov/pubmed/33723486 http://dx.doi.org/10.1016/j.asoc.2021.107285 |
work_keys_str_mv | AT sharmamk mediativefuzzylogicmathematicalmodelacontradictorymanagementpredictionincovid19pandemic AT dhimannitesh mediativefuzzylogicmathematicalmodelacontradictorymanagementpredictionincovid19pandemic AT vandana mediativefuzzylogicmathematicalmodelacontradictorymanagementpredictionincovid19pandemic AT mishravishnunarayan mediativefuzzylogicmathematicalmodelacontradictorymanagementpredictionincovid19pandemic |