Mediative fuzzy logic mathematical model: A contradictory management prediction in COVID-19 pandemic

M K Sharma; Nitesh Dhiman; Vandana; Vishnu Narayan Mishra

doi:10.1016/j.asoc.2021.107285

Mediative fuzzy logic mathematical model: A contradictory management prediction in COVID-19 pandemic

Appl Soft Comput. 2021 Jul:105:107285. doi: 10.1016/j.asoc.2021.107285. Epub 2021 Mar 9.

Authors

M K Sharma¹, Nitesh Dhiman¹, Vandana², Vishnu Narayan Mishra³

Affiliations

¹ Department of Mathematics, C.C.S. University, Meerut 250004, India.
² Department of Computer Application, SCRIET, C.C.S. University, Meerut 250004, India.
³ Department of Mathematics, Indira Gandhi National Tribal University, Lalpur, Amarkantak, Anuppur, Madhya Pradesh 484 887, India.

Abstract

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.

Keywords: Correlation coefficient; Fuzzy logic; Intuitionistic fuzzy correlation; Mediative Fuzzy correlation, COVID-19, Valuation method.