Open Access

ARTICLE

New Ranking of Generalized Quadrilateral Shape Fuzzy Number Using Centroid Technique

A. Thiruppathi^*, C. K. Kirubhashankar

Department of Mathematics, Sathyabama Institute of Science and Technology, Chennai, 600119, Tamilnadu, India

* Corresponding Author: A. Thiruppathi. Email:

Intelligent Automation & Soft Computing 2023, 36(2), 2253-2266. https://doi.org/10.32604/iasc.2023.033870

Received 30 June 2022; Accepted 22 September 2022; Issue published 05 January 2023

Abstract

The output of the fuzzy set is reduced by one for the defuzzification procedure. It is employed to provide a comprehensible outcome from a fuzzy inference process. This page provides further information about the defuzzification approach for quadrilateral fuzzy numbers, which may be used to convert them into discrete values. Defuzzification demonstrates how useful fuzzy ranking systems can be. Our major purpose is to develop a new ranking method for generalized quadrilateral fuzzy numbers. The primary objective of the research is to provide a novel approach to the accurate evaluation of various kinds of fuzzy integers. Fuzzy ranking properties are examined. Using the counterexamples of Lee and Chen demonstrates the fallacy of the ranking technique. So, a new approach has been developed for dealing with fuzzy risk analysis, risk management, industrial engineering and optimization, medicine, and artificial intelligence problems: the generalized quadrilateral form fuzzy number utilizing centroid methodology. As you can see, the aforementioned scenarios are all amenable to the solution provided by the generalized quadrilateral shape fuzzy number utilizing centroid methodology. It’s laid out in a straightforward manner that’s easy to grasp for everyone. The rating method is explained in detail, along with numerical examples to illustrate it. Last but not least, stability evaluations clarify why the Generalized quadrilateral shape fuzzy number obtained by the centroid methodology outperforms other ranking methods.

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