决策模型中Atanassov直觉模糊集的新传递性

IF 1.6 4区计算机科学 Q3 AUTOMATION & CONTROL SYSTEMS

International Journal of Applied Mathematics and Computer Science Pub Date : 2021-12-01 DOI:10.34768/amcs-2021-0038

Barbara Pekala, Piotr Grochowalski, E. Szmidt

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引用次数: 1

摘要

Atanassov的直觉模糊集，特别是直觉模糊关系，是对现实生活中遇到的不完全信息进行有效建模的工具。本文从认识论的角度讨论了阿塔纳索夫直觉模糊关系及物性问题的新概念。传递性反映了偏好关系的一致性。因此，从实际问题出现的角度来看，传递性是很重要的，例如在偏好程序的群体决策中。本文提出了一种新的乐观和悲观传递性，并将其应用于群体决策问题的备选排序过程中。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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New transitivity of Atanassov’s intuitionistic fuzzy sets in a decision making model

Abstract Atanassov’s intuitionistic fuzzy sets and especially his intuitionistic fuzzy relations are tools that make it possible to model effectively imperfect information that we meet in many real-life situations. In this paper, we discuss the new concepts of the transitivity problem of Atanassov’s intuitionistic fuzzy relations in an epistemic aspect. The transitivity property reflects the consistency of a preference relation. Therefore, transitivity is important from the point of view of real problems appearing, e.g., in group decision making in preference procedures. We propose a new type of optimistic and pessimistic transitivity among the alternatives (options) considered and their use in the procedure of ranking the alternatives in a group decision making problem.

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来源期刊

International Journal of Applied Mathematics and Computer Science 工程技术-计算机：人工智能

CiteScore

4.10

自引率

21.10%

发文量

审稿时长

4.2 months

期刊介绍： The International Journal of Applied Mathematics and Computer Science is a quarterly published in Poland since 1991 by the University of Zielona Góra in partnership with De Gruyter Poland (Sciendo) and Lubuskie Scientific Society, under the auspices of the Committee on Automatic Control and Robotics of the Polish Academy of Sciences. The journal strives to meet the demand for the presentation of interdisciplinary research in various fields related to control theory, applied mathematics, scientific computing and computer science. In particular, it publishes high quality original research results in the following areas: -modern control theory and practice- artificial intelligence methods and their applications- applied mathematics and mathematical optimisation techniques- mathematical methods in engineering, computer science, and biology.