从半三元决策空间到三元决策空间的基于模糊含义的转换方法及其应用

IF 3.2 3区 计算机科学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE International Journal of Approximate Reasoning Pub Date : 2024-09-13 DOI:10.1016/j.ijar.2024.109296
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引用次数: 0

摘要

三向决策空间作为三向决策的重要组成部分,极大地丰富了其理论发展和应用前景。同时,模糊蕴涵作为模糊逻辑连接词中的重要一类,为解决实际问题,尤其是复杂决策问题做出了巨大贡献。本文认为二者的协同作用,为模糊蕴涵和三向决策空间的理论发展和应用前景注入了新的活力。作为三向决策空间的重要组成部分,基于模糊逻辑连接词的(半)决策评价函数已被广泛研究,成为研究热点。具体而言,本文主要研究基于模糊蕴涵的从半三向决策空间到三向决策空间的转化方法及其应用。首先,我们提出了从半决策评价函数到决策评价函数的一些新颖的基于模糊含义的变换方法,以及涉及现有半决策评价函数、模糊集、区间值模糊集和模糊关系的半决策评价函数的构造方法。其次,我们讨论了我们的方法与已知三向决策空间构建方法之间的关系。值得注意的是,除了基于非矩阵的方法外,我们的方法涵盖了所有现有方法。最后,通过实验结果,我们得出我们的方法是可行的、有效的,优于已知的三向决策空间方法,并具有良好的抗噪声能力。而且,我们的方法的参数 ρ 也是有效和稳定的。
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Fuzzy implications-based transformation approaches from semi-three-way decision spaces to three-way decision spaces and their applications

Three-way decision spaces, as an important component of three-way decisions, greatly enrich their theoretical development and application prospects. Meanwhile, fuzzy implications, as a vital class of fuzzy logic connectives, have made great contributions to the solution of practical problems, especially complex decision-making problems. This paper considers the collaborative effect of the two, which inject new vitality into the theoretical development and application prospects of fuzzy implications and three-way decision spaces. As a vital component of three-way decision spaces, (semi-)decision evaluation functions have been widely studied based on fuzzy logic connectives and become a research hotspot. Specifically, this paper focuses on fuzzy implications-based transformation approaches from semi-three-way decision spaces to three-way decision spaces and their applications. Firstly, we present some novel fuzzy implications-based transformation approaches from semi-decision evaluation functions to decision evaluation functions, and construction approaches of semi-decision evaluation functions involving the existing semi-decision evaluation functions, fuzzy sets, interval-valued fuzzy sets and fuzzy relations. Secondly, we discuss the relationship between our approaches and the known construction approaches of three-way decision spaces. Notably, our approaches cover all existing approaches except the uninorms-based approaches. Finally, by the experiment results, we obtain our approaches are feasible, effective, superior to the known three-way decision spaces approaches and have good anti-noise ability. And, the parameter ρ of our approaches is also effective and stable.

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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.
期刊最新文献
Belief rule learning and reasoning for classification based on fuzzy belief decision tree Chain graph structure learning based on minimal c-separation trees Three-way conceptual knowledge updating in incomplete contexts Approximations of system W for inference from strongly and weakly consistent belief bases Fuzzy implications-based transformation approaches from semi-three-way decision spaces to three-way decision spaces and their applications
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