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Journal of Fuzzy Logic and Modeling in Engineering

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ISSN (Print): 2666-2949
ISSN (Online): 2666-2957

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Research Article

A Robust Fuzzy Decision Making on Global Warming

Author(s): Kousik Bhattacharya, Sujit Kumar De and Prasun Kumar Nayak

Volume 1, Issue 1, 2022

Published on: 22 December, 2020

Article ID: e010621189358 Pages: 10

DOI: 10.2174/2666294901999201222150703

Price: $65

Abstract

Background: In this article we develop a global warming indicator model under fuzzy system. It is the light of the sun that environmental pollution is responsible for the cause and immediate effect of global warming. Limited amount of oxygen in the air, continuous decrease of fresh water volume, more especially the amount of drinking water and the rise of temperature of the globe are the major symptoms (variants) of global warming. Thus, to capture the facts we need to develop a mathematical model which has not yet been developed by the earlier researchers.

Introduction: An efficient literature survey has been done over the three major parameters of the environment namely oxygen, fresh water and surface temperature exclusively. In fact we have accumulated 150 years-data structure of these major components and have analyzed them under fuzzy system.

Methods: First of all, we gave few definitions on fuzzy set. Utilizing the data set we have constructed appropriate membership functions of the three major components of the environment. Then applying goal programming problem, we have constructed a fuzzy global warming indicator (GWI) model subject to some goal constraints with respective priority vectors (Scenario 1 and Scenario 2). An extension has also been included for multi-valued goal programming problem and numerical illustrations have been done with the help of LINGO software.

Results: Numerical study reveals that the GWI takes maximum and minimum values in a decreasing manner as time increases. It is seen that for scenario 1, the global environmental system will attain its stability after 30 years by degrading 31% of GWI with respect to present base line. For scenario 2, after the same time the global environmental system will attain its stability quite slowly by degrading 28% of GWI with respect to present base line.

Conclusion: Here we have studied a mathematical model of global warming first time using fuzzy system. No other mathematical models have been found existing in the literature. Thus, the basic novelty lies in a robust decision-making approach which showed the expected time of extinction of major species in this world. However, extensive study on data analytics over major environmental components can tell the stability of the global warming indicator and hence the future fate of the globe also.

Keywords: Global warming, goal programming, model development, fuzzy systems, decision making, LINGO.

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