(2007-6024) Ranking of generalized fuzzy numbers based on accuracy of comparison

IF 1.9 4区数学 Q1 MATHEMATICS

Iranian Journal of Fuzzy Systems Pub Date : 2021-05-17 DOI:10.22111/IJFS.2021.6164

M. A. Firozja, F. R. Balf, B. Agheli, R. Chutia

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引用次数: 2

Abstract

Ranking generalized fuzzy numbers plays an important role in many applied models and, in particular, decision-making procedures. In ranking process of two generalized fuzzy numbers, it is natural to compare the sets of values in support of two the generalised fuzzy numbers. Accordingly, the comparison of a real number and a generalised fuzzy number as well as two generalised fuzzy numbers have to be considered. On the other hand, it is seen that a definitive process of comparison of a real number and a generalised fuzzy number, as well as two generalised fuzzy numbers, is not possible. So in this study, a method for comparing a real number and a generalised fuzzy number with a degree of accuracy (between a zero and one) is defined and then the method is generalized to compare two generalised fuzzy numbers. In general, an index to rank a real number and generalised fuzzy number is constructed. Eventually, this index is extended to rank two generalised fuzzy numbers based on the concept of accuracy of comparison. The advantage of our method is that it can compare two generalised fuzzy numbers with an accuracy of comparison. Also, a definition is introduced to make a definitive comparison. Finally, the proposed method is illustrated by some numerical examples.

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(2007-6024)基于比较精度的广义模糊数排序

广义模糊数排序在许多应用模型中，特别是在决策过程中起着重要的作用。在两个广义模糊数的排序过程中，很自然地要比较支持两个广义模糊数的值集。因此，必须考虑实数与广义模糊数的比较，以及两个广义模糊数的比较。另一方面，可以看出，一个实数和一个广义模糊数以及两个广义模糊数的确定比较过程是不可能的。因此，在本研究中，定义了一种比较实数和具有一定精度(0到1之间)的广义模糊数的方法，然后将该方法推广到两个广义模糊数的比较。在一般情况下，构造一个对实数和广义模糊数进行排序的指标。最后，根据比较精度的概念，将该指标推广到对两个广义模糊数进行排序。该方法的优点是可以对两个广义模糊数进行比较，且比较精度较高。此外，还引入了一个定义来进行明确的比较。最后，通过数值算例对该方法进行了说明。

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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来源期刊

Iranian Journal of Fuzzy Systems 数学-数学

CiteScore

3.50

自引率

16.70%

发文量

期刊介绍： The two-monthly Iranian Journal of Fuzzy Systems (IJFS) aims to provide an international forum for refereed original research works in the theory and applications of fuzzy sets and systems in the areas of foundations, pure mathematics, artificial intelligence, control, robotics, data analysis, data mining, decision making, finance and management, information systems, operations research, pattern recognition and image processing, soft computing and uncertainty modeling. Manuscripts submitted to the IJFS must be original unpublished work and should not be in consideration for publication elsewhere.