Ranking of Alternatives Described by Atanassov’s Intuitionistic Fuzzy Sets – Reconciling Some Misunderstandings

IF 3.3 3区 计算机科学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Journal of Artificial Intelligence and Soft Computing Research Pub Date : 2024-06-01 DOI:10.2478/jaiscr-2024-0013
E. Szmidt, Janusz Kacprzyk, Paweł Bujnowski, Janusz T. Starczewski, A. Siwocha
{"title":"Ranking of Alternatives Described by Atanassov’s Intuitionistic Fuzzy Sets – Reconciling Some Misunderstandings","authors":"E. Szmidt, Janusz Kacprzyk, Paweł Bujnowski, Janusz T. Starczewski, A. Siwocha","doi":"10.2478/jaiscr-2024-0013","DOIUrl":null,"url":null,"abstract":"Abstract Atanassov’s intuitionistic fuzzy sets (IFSs) are a very convenient tool for describing alternatives/options while making decisions because they make it possible to naturally represent the pros, cons, and hesitation. The IFSs have attracted a significant interest and have been applied in various fields. Of course, their use poses some challenges. One of the main challenges is the ranking of alternatives/options described by the intuitionistic fuzzy sets, to be called for brevity the intuitionistic fuzzy alternatives. This is a crucial issue, notably for the applications, for instance, in decision making. We first present in detail and analyze the benefits of a method we introduced previously (cf. Szmidt and Kacprzyk [1]). For this method, we augment the original assumptions with an additional assumption, which is justified and inherently reasonable. As a result, we obtain formulas which are better justified than those previously used as they explicitly consider the arguments in favor (pro), against (con), and hesitance. Since the intuitionistic fuzzy alternatives can not be linearly ranked, then the additional assumptions during the ranking process are necessary. We address these issues and analyze examples to clarify our new approach. We examine some other methods discussed in the literature and analyze their results, and show that the new assumptions reconcile some misconceptions raised by those other papers.","PeriodicalId":48494,"journal":{"name":"Journal of Artificial Intelligence and Soft Computing Research","volume":null,"pages":null},"PeriodicalIF":3.3000,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Artificial Intelligence and Soft Computing Research","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.2478/jaiscr-2024-0013","RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
引用次数: 0

Abstract

Abstract Atanassov’s intuitionistic fuzzy sets (IFSs) are a very convenient tool for describing alternatives/options while making decisions because they make it possible to naturally represent the pros, cons, and hesitation. The IFSs have attracted a significant interest and have been applied in various fields. Of course, their use poses some challenges. One of the main challenges is the ranking of alternatives/options described by the intuitionistic fuzzy sets, to be called for brevity the intuitionistic fuzzy alternatives. This is a crucial issue, notably for the applications, for instance, in decision making. We first present in detail and analyze the benefits of a method we introduced previously (cf. Szmidt and Kacprzyk [1]). For this method, we augment the original assumptions with an additional assumption, which is justified and inherently reasonable. As a result, we obtain formulas which are better justified than those previously used as they explicitly consider the arguments in favor (pro), against (con), and hesitance. Since the intuitionistic fuzzy alternatives can not be linearly ranked, then the additional assumptions during the ranking process are necessary. We address these issues and analyze examples to clarify our new approach. We examine some other methods discussed in the literature and analyze their results, and show that the new assumptions reconcile some misconceptions raised by those other papers.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
用阿塔纳索夫直觉模糊集描述的替代品排序 - 消除一些误解
摘要 阿塔纳索夫的直觉模糊集(IFS)是一种非常方便的工具,用于描述决策过程中的备选方案/选项,因为它可以自然地表示利弊和犹豫。IFS 已引起了人们的极大兴趣,并已被应用于各个领域。当然,它们的使用也带来了一些挑战。其中一个主要挑战是如何对直觉模糊集(简称为直觉模糊替代方案)所描述的替代方案/选项进行排序。这是一个关键问题,尤其是在决策等应用中。我们首先详细介绍并分析我们之前介绍过的一种方法(参见 Szmidt 和 Kacprzyk [1])的优点。对于这种方法,我们在原有假设的基础上增加了一个额外的假设,这个假设是合理的,本质上也是合理的。因此,我们得到的公式比以前使用的公式更合理,因为它们明确考虑了赞成(pro)、反对(con)和犹豫不决的论据。由于直觉模糊替代方案无法进行线性排序,因此在排序过程中需要额外的假设。我们将解决这些问题,并通过实例分析来阐明我们的新方法。我们研究了文献中讨论的其他一些方法,并分析了它们的结果,结果表明新的假设调和了其他论文中提出的一些误解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
Journal of Artificial Intelligence and Soft Computing Research
Journal of Artificial Intelligence and Soft Computing Research COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-
CiteScore
7.00
自引率
25.00%
发文量
10
审稿时长
24 weeks
期刊介绍: Journal of Artificial Intelligence and Soft Computing Research (available also at Sciendo (De Gruyter)) is a dynamically developing international journal focused on the latest scientific results and methods constituting traditional artificial intelligence methods and soft computing techniques. Our goal is to bring together scientists representing both approaches and various research communities.
期刊最新文献
Sinextnet: A New Small Object Detection Model for Aerial Images Based on PP-Yoloe A Hybrid Equilibrium Optimizer Based on Moth Flame Optimization Algorithm to Solve Global Optimization Problems Optimizing the Structures of Transformer Neural Networks Using Parallel Simulated Annealing Ranking of Alternatives Described by Atanassov’s Intuitionistic Fuzzy Sets – Reconciling Some Misunderstandings Shufflemono: Rethinking Lightweight Network for Self-Supervised Monocular Depth Estimation
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1