research-article

A necessary condition for comparing and ranking of triangular fuzzy numbers on the basis of height-independent ranking techniques

Author: Alireza Sotoudeh-AnvariAuthors Info & Claims

International Journal of Knowledge-based and Intelligent Engineering Systems, Volume 24, Issue 4

Pages 269 - 277

https://doi.org/10.3233/KES-180163

Published: 01 January 2020 Publication History

Abstract

The open problem of comparing fuzzy numbers as one of the most important issues in fuzzy sets has been studied by many researchers. However, this problem has not been solved up to now and perhaps it will never be fully answered. This work proposes a necessary condition for ranking of triangular fuzzy numbers on the basis of some efficient height-independent ranking methods such as centroids, total integral value, signed distance and defuzzification. To the best of our knowledge, this paper provides the first use of a necessary condition in ranking methods. Fortunately, suggested approach is very straightforward, fast and efficient to use in the real problems. To evaluate the suggested approach with the result of existing methods, six examples are presented. Finally, we apply this necessary condition for ranking fuzzy numbers to a fuzzy failure mode and effect analysis (FMEA) problem. The results show that our approach is practical and has reasonable outcome.

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Cited By

Sotoudeh-Anvari MSotoudeh-Anvari A(2023)Setback in ranking fuzzy numbers: a study in fuzzy risk analysis in diabetes predictionArtificial Intelligence Review10.1007/s10462-022-10282-656:5(4591-4639)Online publication date: 1-May-2023
https://dl.acm.org/doi/10.1007/s10462-022-10282-6

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A necessary condition for comparing and ranking of triangular fuzzy numbers on the basis of height-independent ranking techniques

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cover image International Journal of Knowledge-based and Intelligent Engineering Systems

International Journal of Knowledge-based and Intelligent Engineering Systems Volume 24, Issue 4

2020

105 pages

ISSN:1327-2314

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© 2020 – IOS Press and the authors. All rights reserved.

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IOS Press

Netherlands

Publication History

Published: 01 January 2020

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Cited By

Sotoudeh-Anvari MSotoudeh-Anvari A(2023)Setback in ranking fuzzy numbers: a study in fuzzy risk analysis in diabetes predictionArtificial Intelligence Review10.1007/s10462-022-10282-656:5(4591-4639)Online publication date: 1-May-2023
https://dl.acm.org/doi/10.1007/s10462-022-10282-6

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