加权多粒度直觉模糊信息系统的粗糙集模型及其决策<sup>*</sup>

doi:10.16451/j.cnki.issn1003-6059.201711002

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摘要针对现有多粒度直觉模糊粗糙集决策模型的不足,提出粒度加权的多粒度直觉模糊粗糙集模型.首先研究加权多粒度直觉模糊粗糙集的基本性质,分析加权多粒度直觉模糊粗糙集与乐观多粒度、悲观多粒度直觉模糊粗糙集之间的关系,并给出这几种模型不确定度量之间的关系.然后给出决策规则的置信度和支持度定义以及决策规则的获取方法,弥补目前常用的多粒度直觉模糊粗糙集的不足.最后通过决策实例分析验证文中模型的有效性.

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	纪霞
	赵鹏
	姚晟

关键词 ：直觉模糊信息系统, 多粒度粗糙集, 加权, 置信度, 支持度

Abstract：By analyzing the limitation of the current multi-granulation intuitionistic fuzzy rough set(MGIFRS), a MGIFRS based on weighted granulations is presented in this paper. Firstly, the properties of the presented MGIFRS are analyzed. Three intuitionistic fuzzy rough sets, MGIFRS based on weighted granulations, optimistic MGIFRS and pessimistic MGIFRS, are compared to declare their relationships, and the relationship of uncertainty measurements under these three kinds of MGIFRS are also discussed. Then, the certainty factor and support factor of the decision rule are defined. A rule acquisition method is provided to make up for the shortcomings of the existing MGIFRS. Finally, an decision-making example is utilized to verify the validity of the proposed MGIFRS based on weighted granulations.

Key words： Intuitionistic Fuzzy Information System Multi-granulation Rough Set Weighting Certainty Factor Support Factor

收稿日期: 2017-03-05

ZTFLH:

TP 18

基金资助:国家自然科学基金项目(No.61602004,61300057)、安徽省自然科学基金项目(No.1408085MF122,1508085MF127)、安徽省高校自然科学基金项目(No.KJ2017A011,KJ2016A041)、安徽大学计算智能与信号处理教育部重点实验室项目、安徽大学信息保障技术协同创新中心课题资助

作者简介: 纪霞(通讯作者),女,1982年生,博士,讲师,主要研究方向为数据挖掘、粗糙集理论、机器学习.E-mail:jixia1983@163.com.
赵鹏,女,1976年生,博士,副教授, 主要研究方向为智能信息处理.E-mail: zhaopeng_ad@163.com.
姚晟,女,1979年生,博士,讲师,主要研究方向为粗糙集、粒计算、大数据.E-mail: fisheryao@126.com.

引用本文:

纪霞，赵鹏，姚晟. 加权多粒度直觉模糊信息系统的粗糙集模型及其决策^*[J]. 模式识别与人工智能, 2017, 30(11): 971-982. JI Xia, ZHAO Peng, YAO Sheng. Rough Set Model and Decision Research in Intuitionistic Fuzzy Information System Based on Weighted Multi-granulation. , 2017, 30(11): 971-982.

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