[1]梁美社,米据生,张少谱.双论域上的广义直觉模糊概率粗糙集模型及其应用[J].智能系统学报,2022,17(3):585-592.[doi:10.11992/tis.202106025]
LIANG Meishe,MI Jusheng,ZHANG Shaopu.Generalized intuitionistic fuzzy probabilistic rough set models on two universes and their applications[J].CAAI Transactions on Intelligent Systems,2022,17(3):585-592.[doi:10.11992/tis.202106025]
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LIANG Meishe,MI Jusheng,ZHANG Shaopu.Generalized intuitionistic fuzzy probabilistic rough set models on two universes and their applications[J].CAAI Transactions on Intelligent Systems,2022,17(3):585-592.[doi:10.11992/tis.202106025]
双论域上的广义直觉模糊概率粗糙集模型及其应用
《智能系统学报》[ISSN 1673-4785/CN 23-1538/TP] 卷:
17
期数:
2022年第3期
页码:
585-592
栏目:
学术论文—人工智能基础
出版日期:
2022-05-05
- Title:
- Generalized intuitionistic fuzzy probabilistic rough set models on two universes and their applications
- Keywords:
- two universes; rough set; intuitionistic fuzzy relations; probabilistic rough set; intuitionistic fuzzy sets; intuitionistic fuzzy probabilistic approximation spaces; lower approximation; upper approximation
- 分类号:
- TP391
- 摘要:
- 已有的双论域直觉模糊概率粗糙集模型通过设置两个阈值${\lambda _1}$、${\lambda _2} $，讨论了经典集合在直觉模糊二元关系下的概率粗糙下上近似。该模型不能计算直觉模糊集合在直觉模糊二元关系下的概率粗糙下上近似，这在一定程度上限制了该模型的应用。首先给出了直觉模糊条件概率的定义。在直觉模糊概率空间下构造了双论域广义直觉模糊概率粗糙集模型，讨论了模型的主要性质。最后，将模型应用到临床诊断系统中。与其他模型相比，所提出的广义直觉模糊概率粗糙集模型进一步丰富了概率粗糙集理论，更适合于实际应用。
- Abstract:
- In the existing intuitionistic fuzzy (IF) probabilistic rough set model of two universes, the probabilistic rough lower and upper approximations of a classical set under IF binary relation are discussed by setting two thresholds, ${\lambda _1}\;{\rm{and}}\;{\lambda _2}$. However, this model is unable to calculate the probabilistic rough lower and upper approximations of IF sets under IF binary relation, which limits the application of this model to a certain extent. In this study, we first define the IF conditional probability. Then, the generalized IF probability rough set models are constructed in IF probabilistic approximation space. In addition, the main properties of the model are discussed. Finally, the numerical examples of clinical diagnostic systems are applied to illustrate the validity of the proposed models. Compared with other models, the proposed generalized IF probabilistic rough set models further enrich the probabilistic rough set theory and are more suitable for practical applications.
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备注/Memo
收稿日期:2021-06-16。
基金项目:国家自然科学基金项目(62076088)；河北省自然科学基金项目(A2020208004).
作者简介:梁美社，副教授，博士，主要研究方向为粗糙集理论、粒计算。发表学术论文20篇;米据生，教授，博士生导师，博士，主要研究方向为粗糙集、概念格、近似推理。主持国家自然科学基金面上项目4项,获得省级自然科学奖3项。发表学术论文150余篇，多次入选爱思唯尔发布的中国高被引学者榜单（计算机科学领域）;张少谱，教授，博士，主要研究方向为可靠性数学与数据挖掘
通讯作者:梁美社.E-mail：liangmeishe@163.com
更新日期/Last Update:
1900-01-01