粗糙集的两种相似性度量

doi:10.11896/j.issn.1002-137X.2015.06.022

计算机科学 ›› 2015, Vol. 42 ›› Issue (6): 97-100.doi: 10.11896/j.issn.1002-137X.2015.06.022

• 第十届和谐人机环境联合学术会议 • 上一篇下一篇

粗糙集的两种相似性度量

林娟,米据生,解滨

河北师范大学数学与信息科学学院石家庄050024,河北师范大学数学与信息科学学院石家庄050024,河北师范大学数学与信息科学学院石家庄050024;河北师范大学信息技术学院石家庄050024

出版日期:2018-11-14 发布日期:2018-11-14
基金资助:
本文受国家自然科学基金(61170107,3,61300121),河北省高校创新团队领军人才培育计划项目(LJRC022),河北省自然科学基金(A2014205157)资助

Two Similarity Measures between Rough Sets

LIN Juan, MI Ju-sheng and XIE Bin

Online:2018-11-14 Published:2018-11-14

摘要/Abstract

摘要： 粗糙集理论是一种新的处理模糊和不确定性知识的软计算工具。在近似空间中,首先基于集合的上下近似给出了一种粗糙集间的相似度量方法。然后通过定义一种基于粗糙隶属函数的包含度,给出了另外一种粗糙集间的相似度量方法,并分别研究了这两种相似度量方法的有关性质。最后讨论了这两种相似度量方法之间的关系。

关键词: 粗糙集,上下近似,包含度,相似度量

Abstract: Rough set theory is emerging as a powerful tool for dealing with vagueness and uncertainty of knowledge.First of all,one method of measuring the similarity between two rough sets was proposed in approximate space based on approximation sets.And then an inclusion degree was defined based on rough membership function,which was used to define another similarity measure between two rough sets.The properties of the two similarity measures were studied respectively.Finally,the relationship between the two similarity measures was also discussed.

Key words: Rough set,Lower and upper approximation,Inclusion degree,Similarity measure

林娟,米据生,解滨. 粗糙集的两种相似性度量[J]. 计算机科学, 2015, 42(6): 97-100. https://doi.org/10.11896/j.issn.1002-137X.2015.06.022

LIN Juan, MI Ju-sheng and XIE Bin. Two Similarity Measures between Rough Sets[J]. Computer Science, 2015, 42(6): 97-100. https://doi.org/10.11896/j.issn.1002-137X.2015.06.022

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粗糙集的两种相似性度量

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