[1]徐健锋,王书谊,姚一豫,等.三支决策的可视化概念与分析[J].智能系统学报,2026,21(2):542-552.[doi:10.11992/tis.202507014]
XU Jianfeng,WANG Shuyi,YAO Yiyu,et al.Visualization concepts and analysis of three-way decisions[J].CAAI Transactions on Intelligent Systems,2026,21(2):542-552.[doi:10.11992/tis.202507014]
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XU Jianfeng,WANG Shuyi,YAO Yiyu,et al.Visualization concepts and analysis of three-way decisions[J].CAAI Transactions on Intelligent Systems,2026,21(2):542-552.[doi:10.11992/tis.202507014]
三支决策的可视化概念与分析
《智能系统学报》[ISSN 1673-4785/CN 23-1538/TP] 卷:
21
期数:
2026年第2期
页码:
542-552
栏目:
学术论文—人工智能基础
出版日期:
2026-03-05
- Title:
- Visualization concepts and analysis of three-way decisions
- Keywords:
- three-way decisions; decision-theoretic rough sets; Bayesian risk theory; three-way concept analysis; visualization; probabilistic rough sets; double-quantitative; geometric interpretation
- 分类号:
- TP182
- 摘要:
- 三支决策是一种不确定问题求解新型理论，如何提升该理论体系的可解释性是其重要研究方向之一。可视化技术是计算机科学领域重要的可解释性手段，在三支决策相关研究中尚未开展系统的可视化理论研究，亟需可解释性较强的可视化研究工具。因此，本文基于三支决策的经典模型，提出了一套三支决策可视化建模和推理方法。本文在三支决策的基本概念可视化描述基础上，针对决策理论粗糙集的可视化问题，构造了一种概率-代价可视化空间，分别对三支代价目标函数在可视化空间中的几何语义及其单调性进行可视化解读，并在此基础上对三支决策的各个阈值进行可视化推导；在上述研究基础上针对双量化三支决策的可视化问题，进一步构建了相对条件概率-绝对条件概率可视化二维空间，并在该二维空间中对9种双量化决策类型进行了可视化分析。最后，本文通过一个蘑菇实例验证了所提出的三支可视化方法能够为复杂不确定性推理提供有效可解释性决策支撑，填补了三支决策领域在系统性可视化理论研究上的空白，显示了较好的推广和应用价值。
- Abstract:
- Three-way decision is a novel theory for solving uncertain problems, and enhancing its interpretability is a key research direction. While visualization is a powerful means of achieving interpretability in computer science, a systematic theoretical framework for visualizing three-way decisions has not yet been established, creating an urgent need for highly interpretable visualization tools. Therefore, based on the classic models of three-way decisions, this paper proposes a set of methods for visual modeling and reasoning. Firstly, building on a visual representation of the fundamental concepts, this paper addresses the visualization of Decision-Theoretic Rough Sets (DTRS) by constructing a Probability-Cost visualization space. Within this space, the geometric semantics and monotonicity of the three cost-objective functions are visually interpreted, which in turn enables a visual derivation of the decision thresholds. Secondly, extending this work to the visualization of Double-Quantitative Three-Way Decisions (DQ-TWD), we further construct a two-dimensional Relative Conditional Probability-Absolute Conditional Probability space for the visual analysis of the nine double-quantitative decision types. Finally, a case study using a mushroom dataset verifies that the proposed visualization tools provide effective and interpretable decision support for complex uncertain reasoning applications, demonstrating strong potential for generalization and practical application.
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备注/Memo
收稿日期:2025-7-10。
基金项目:国家自然科学基金项目（62266032）.
作者简介:徐健锋，教授，南昌大学智慧医疗研究院常务副院长，江西省虚拟现实重点实验室副主任，中国人工智能学会粒计算与知识发现专委会委员，江西省03专项专家组特聘专家，江西省首届教育数字化专家委员会首席专家，中国知网高被引学者。主要研究方向为人工智能、智慧医疗、粒计算和流计算。近5年主持国家自然科学基金项目2项、国家重大专项子课题任务1项、省厅级纵向课题7项、企业横向课题50余项。获江西省科技进步二等奖，获省级教学成果二等奖1项，校级教学成果奖6项，省级精品课程1项。获发明专利授权16项。发表学术论文90余篇。E-mail：jianfeng_x@ncu.edu.cn。;王书谊，硕士研究生，主要研究方向为粒计算和不确定性人工智能。E-mail：w592969166@126.com。;姚一豫，加拿大里贾纳大学计算机科学系教授、博士生导师。主要研究方向为决策粗糙集、粒计算。提出三支决策理论、粒计算三元论，提出决策粗糙集理论，网络智能研究领域发起者之一。《International Journal of ApproximateReasoning》区域编辑，《Information Sciences》和《Knowledge-based Systems》副主编，8个国际刊物的编委会成员，国际粗糙集协会副主席。2008年获PAKDD最具影响力论文奖(1999-2008)，2010年获中国人工智能学会粗糙集与软计算专业委员会华侨友谊奖，2014年获里贾那大学校友会杰出科研奖，2015年全球高被引科学家。从1992年至今，连续获得加拿大自然科学与工程基金项目资助。发表学术论文300多篇；与其他学者合作出版专著10多部。E-mail：Yiyu.Yao@uregina.ca。
通讯作者:徐健锋. E-mail：jianfeng_x@ncu.edu.cn
更新日期/Last Update:
1900-01-01