A multi-strategy three-way decision approach for tri-state risk loss under q-rung orthopair fuzzy environment

IF 7.2 1区 计算机科学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
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Abstract

Addressing the decision-making challenge arising from the uncertainty of human cognition, three-way decision (3WD) and q-rung orthopair fuzzy sets (q-ROFSs) are integrated in this paper to propose a multi-strategy three-way decision approach (MS3WDA) for tri-state risk loss (TSRL) under q-rung orthopair fuzzy environment. Based on the ternary thinking of human cognition, the risk loss with hesitation state is considered and constructed under q-rung orthopair fuzzy environment. The TSRL with hesitation state is further constructed by combining the q-rung orthopair fuzzy (q-ROF) information. The conditional probability adopted by the original object classes is improved and extended by the three components of q-ROFSs. Next, the TSRL with q-ROF information and three components of q-ROFSs are integrated with decision-theoretic rough sets (DTRSs) to establish a novel 3WD model. Some relevant properties are also analyzed and discussed for the developed 3WD model. Then, its multi-strategy decision method is proposed based on the multi-strategy perspective. The related strategies with five different levels are designed by considering three different risk appetite perspectives and four different aspects of q-ROF information. The relevant threshold theorems are also given and proved to further provide the theoretical support for our MS3WDA. According to the five different strategies, we further derive the corresponding decision rules of MS3WDA. The key steps and specific algorithm are summarized for MS3WDA. Finally, a case study is provided to demonstrate the practicability and feasibility of MS3WDA. Meanwhile, the rationality, robustness and superiority of MS3WDA are further validated by the sensitivity analysis and comparative analysis.

q-rung正交模糊环境下三态风险损失的多策略三向决策方法
针对人类认知的不确定性所带来的决策挑战,本文将三向决策(3WD)与q-rung正交模糊集(q-ROFSs)相结合,提出了一种在q-rung正交模糊环境下针对三态风险损失(TSRL)的多策略三向决策方法(MS3WDA)。基于人类认知的三元思维,考虑并构建了 q-rung orthopair 模糊环境下具有犹豫状态的风险损失。结合 q-rung orthopair 模糊(q-ROF)信息,进一步构建了具有犹豫状态的 TSRL。原始对象类别所采用的条件概率通过 q-ROFS 的三个分量进行了改进和扩展。接下来,带有 q-ROF 信息的 TSRL 和 q-ROFSs 的三个组成部分与决策理论粗糙集(DTRSs)相结合,建立了一个新的 3WD 模型。此外,还对所建立的 3WD 模型的一些相关特性进行了分析和讨论。然后,基于多策略视角提出了多策略决策方法。通过考虑三种不同的风险偏好视角和 q-ROF 信息的四个不同方面,设计了五个不同层次的相关策略。同时给出并证明了相关的阈值定理,进一步为我们的 MS3WDA 提供了理论支持。根据五种不同的策略,我们进一步推导出 MS3WDA 的相应决策规则。总结了 MS3WDA 的关键步骤和具体算法。最后,通过案例研究证明了 MS3WDA 的实用性和可行性。同时,通过灵敏度分析和对比分析,进一步验证了 MS3WDA 的合理性、稳健性和优越性。
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来源期刊
Applied Soft Computing
Applied Soft Computing 工程技术-计算机:跨学科应用
CiteScore
15.80
自引率
6.90%
发文量
874
审稿时长
10.9 months
期刊介绍: Applied Soft Computing is an international journal promoting an integrated view of soft computing to solve real life problems.The focus is to publish the highest quality research in application and convergence of the areas of Fuzzy Logic, Neural Networks, Evolutionary Computing, Rough Sets and other similar techniques to address real world complexities. Applied Soft Computing is a rolling publication: articles are published as soon as the editor-in-chief has accepted them. Therefore, the web site will continuously be updated with new articles and the publication time will be short.
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