基于遗憾的支配三方决策模型与环形球面模糊 Mahalanobis 距离

IF 8.1 1区 计算机科学 0 COMPUTER SCIENCE, INFORMATION SYSTEMS
Shahzaib Ashraf , Chiranjibe Jana , Wania Iqbal , Muhammet Deveci
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引用次数: 0

摘要

本文提出了一个革命性的三向多属性模型,以应对决策过程中日益增加的复杂性和风险。该模型将三向决策规则与具有影响力的后悔和前景行为理论相结合。为了解决评估数据中的不确定性,本文将圆球形模糊集无缝集成到信息系统中,并指出这种方法也可顺利应用于圆盘球形模糊集(D-SFS)。此外,还引入了一种利用相关系数和方差进行属性加权的开创性方法。传统的 Mahalanobis 距离被扩展为圆形、球形、模糊 Mahalanobis 距离。根据环形球面模糊集(C-SFS)中不同的基于遗憾的支配关系和基于欣喜的支配关系,开发了一种估算条件概率的新方法。此外,基于前景理论的三种评分系统得出了绝望型、期望型和平衡型决策策略,为了解决策者的各种心态提供了无价之宝。此外,为了说明这些方法与 D-SFSs 信息的实际应用,我们利用 D-SFSs 解决了一个实例。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Regret-based domination three-way decision-making model with circular spherical fuzzy Mahalanobis distance
This article proposes a revolutionary three-way multi-attribute model in response to the increased complexity and risk in decision-making processes. This model combines three-way decision rules with the influential behavioral theories of regret and prospect. To address uncertainties in evaluation data, a circular spherical fuzzy set is seamlessly integrated into the information system, noting that this method can also be smoothly applied to disc spherical fuzzy sets (D-SFSs). Moreover, a pioneering method utilizing correlation coefficients and variances is introduced for attribute weighting. The conventional Mahalanobis distance is extended to a circular, spherical, fuzzy Mahalanobis distance. A novel approach is developed to estimate conditional probabilities based on the distinct regret-based dominating and rejoice-based dominating relations in circular spherical fuzzy sets (C-SFSs). Additionally, three scoring systems based on prospect theory yield despondent, expectant, and balanced decision-making strategies and provide priceless insights into various decision-maker mindsets. Furthermore, to illustrate the practical application of these methods with D-SFSs information, an example has been solved utilizing D-SFSs.
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来源期刊
Information Sciences
Information Sciences 工程技术-计算机:信息系统
CiteScore
14.00
自引率
17.30%
发文量
1322
审稿时长
10.4 months
期刊介绍: Informatics and Computer Science Intelligent Systems Applications is an esteemed international journal that focuses on publishing original and creative research findings in the field of information sciences. We also feature a limited number of timely tutorial and surveying contributions. Our journal aims to cater to a diverse audience, including researchers, developers, managers, strategic planners, graduate students, and anyone interested in staying up-to-date with cutting-edge research in information science, knowledge engineering, and intelligent systems. While readers are expected to share a common interest in information science, they come from varying backgrounds such as engineering, mathematics, statistics, physics, computer science, cell biology, molecular biology, management science, cognitive science, neurobiology, behavioral sciences, and biochemistry.
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