New Ranking of Generalized Quadrilateral Shape Fuzzy Number Using Centroid Technique  

作　　者：A.Thiruppathi C.K.Kirubhashankar 

机构地区：[1]Department of Mathematics,Sathyabama Institute of Science and Technology,Chennai,600119,Tamilnadu,India

出　　处：《Intelligent Automation & Soft Computing》2023年第5期2253-2266,共14页智能自动化与软计算（英文）

摘　　要：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 defuzzifica-tion 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 gen-eralized quadrilateral fuzzy numbers.The primary objective of the research is to provide a novel approach to the accurate evaluation of various kinds of fuzzy inte-gers.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,indus-trial 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 pro-vided 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 exam-ples to illustrate it.Last but not least,stability evaluations clarify why the Gener-alized quadrilateral shape fuzzy number obtained by the centroid methodology outperforms other ranking methods.

关 键 词：Fuzzy numbers quadrilateral fuzzy number ranking methods fuzzy risk analysis 

分 类 号：O159[理学—数学]