Bipolar decomposition integrals

IF 3.2 3区 计算机科学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Jabbar Abbas , Radko Mesiar , Radomír Halaš
{"title":"Bipolar decomposition integrals","authors":"Jabbar Abbas ,&nbsp;Radko Mesiar ,&nbsp;Radomír Halaš","doi":"10.1016/j.ijar.2025.109439","DOIUrl":null,"url":null,"abstract":"<div><div>The idea of decomposition integral, inspired by the concept of Lebesgue integral, is a common framework for unifying many nonlinear integrals, such as the Choquet, the Shilkret, the PAN, and the concave integrals. This framework concerns aggregation on a unipolar scale, and depends on the distinguished decomposition system under some constraints on the sets being considered for each related integral. The aim of this paper is to provide a general framework to deal with integrals concerning aggregation on unipolar and bipolar scales. To achieve this aim, we propose in this paper an extension of the idea of decomposition integral of the integrated function to be suitable for bipolar scales depending on the distinguished bipolar decomposition system under some constraints on the bipolar collections being considered for each related bipolar fuzzy integral. Then, we introduce some properties of bipolar decomposition integrals, including those establishing that our approach covers the Cumulative Prospect Theory (CPT) model and the integrals with respect to bipolar capacities. Finally, we conclude with certain directions on some additional findings related to the research.</div></div>","PeriodicalId":13842,"journal":{"name":"International Journal of Approximate Reasoning","volume":"183 ","pages":"Article 109439"},"PeriodicalIF":3.2000,"publicationDate":"2025-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Approximate Reasoning","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0888613X25000805","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

The idea of decomposition integral, inspired by the concept of Lebesgue integral, is a common framework for unifying many nonlinear integrals, such as the Choquet, the Shilkret, the PAN, and the concave integrals. This framework concerns aggregation on a unipolar scale, and depends on the distinguished decomposition system under some constraints on the sets being considered for each related integral. The aim of this paper is to provide a general framework to deal with integrals concerning aggregation on unipolar and bipolar scales. To achieve this aim, we propose in this paper an extension of the idea of decomposition integral of the integrated function to be suitable for bipolar scales depending on the distinguished bipolar decomposition system under some constraints on the bipolar collections being considered for each related bipolar fuzzy integral. Then, we introduce some properties of bipolar decomposition integrals, including those establishing that our approach covers the Cumulative Prospect Theory (CPT) model and the integrals with respect to bipolar capacities. Finally, we conclude with certain directions on some additional findings related to the research.
双极分解积分
分解积分的思想是由勒贝格积分的概念启发而来的,是统一许多非线性积分的通用框架,如Choquet、Shilkret、PAN和凹积分。该框架关注的是单极尺度上的聚集,并依赖于对每个相关积分所考虑的集合的某些约束下的区分分解系统。本文的目的是提供一个一般的框架来处理在单极和双极尺度上有关聚集的积分。为了达到这一目的,本文提出了积分函数分解积分思想的扩展,使其适用于双极尺度,这取决于对每个相关的双极模糊积分所考虑的双极集合的某些约束条件下的可区分的双极分解系统。然后,我们介绍了双极分解积分的一些性质,包括建立了我们的方法涵盖了累积前景理论(CPT)模型和关于双极容量的积分。最后,我们对与研究相关的一些其他发现提出了一定的方向。
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 求助全文
来源期刊
International Journal of Approximate Reasoning
International Journal of Approximate Reasoning 工程技术-计算机:人工智能
CiteScore
6.90
自引率
12.80%
发文量
170
审稿时长
67 days
期刊介绍: The International Journal of Approximate Reasoning is intended to serve as a forum for the treatment of imprecision and uncertainty in Artificial and Computational Intelligence, covering both the foundations of uncertainty theories, and the design of intelligent systems for scientific and engineering applications. It publishes high-quality research papers describing theoretical developments or innovative applications, as well as review articles on topics of general interest. Relevant topics include, but are not limited to, probabilistic reasoning and Bayesian networks, imprecise probabilities, random sets, belief functions (Dempster-Shafer theory), possibility theory, fuzzy sets, rough sets, decision theory, non-additive measures and integrals, qualitative reasoning about uncertainty, comparative probability orderings, game-theoretic probability, default reasoning, nonstandard logics, argumentation systems, inconsistency tolerant reasoning, elicitation techniques, philosophical foundations and psychological models of uncertain reasoning. Domains of application for uncertain reasoning systems include risk analysis and assessment, information retrieval and database design, information fusion, machine learning, data and web mining, computer vision, image and signal processing, intelligent data analysis, statistics, multi-agent systems, etc.
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信