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Dynamic Fuzzy Sets and New DFS MADM Technique

Institute of basic and applied science – college of engineering and technology, arab academy for science technology and maritime transport, egypt.

* Corresponding Author
Annals of Communications in Mathematics 2024
, 7 (4),
310-327.
https://doi.org/10.62072/acm.2024.070401
Received: 26 Aug 2024 |
Accepted: 25 Sep 2024 |
Published: 31 Dec 2024

Abstract

Dynamics fuzzy sets outperform fuzzy sets for dealing with unclear situations. There are many applications for fuzzy similarity metrics, including cluster analysis, problem classification, and even medical diagnosis. Lean entropy measurements are essential to determine the weights of the criteria in a situation involving multi-criteria decision-making. In this paper, we introduce and suggest alternative similarity measures for Dynamics fuzzy collections. We developed some new entropy metrics for using recommended similarity assessments. Dynamics fuzzy collections. Finally, in a Dynamics fuzzy environment, a novel multi-attribute decision-making method is developed that solves a significant limitation of the famous decision-making methodology, namely, the technique for order preference by similarity to the ideal solution.

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Cite This Article

Dynamic Fuzzy Sets and New DFS MADM Technique.

Annals of Communications in Mathematics,

2024,
7 (4):
310-327.
https://doi.org/10.62072/acm.2024.070401
  • Creative Commons License
  • Copyright (c) 2024 by the Author(s). Licensee Techno Sky Publications. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).

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