Uncertainty of Rough Sets in Different Knowledge Granularities
Uncertainty of Rough Sets in Different Knowledge Granularities
复制标题
不同知识粒度下粗糙集的不确定性
DOI：
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发表时间：
2008
影响因子：
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通讯作者：
Wang Guo-Yin
中科院分区：
文献类型：
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作者：
Zhang Qing-Hua;Wang Guo-Yin
粗糙度、粗糙熵、模糊性和模糊性是衡量粗糙集不确定性的主要方法。在不同的知识粒度下，提出了一种基于信息系统属性的层次知识空间链。发现粗糙集的粗糙熵和模糊性随知识粒度的变化规律与人类的认知不一致。提出了一种新的基于信息熵的粗糙集模糊性度量方法。该方法所度量的模糊性随着近似空间中知识粒度的细化而单调递减。最后，该方法克服了粗糙和粗糙熵的问题分析了不同知识粒度下粗糙度变化与模糊性的关系。
Rougness,rough entropy,fuzziness,and fuzzy entropy are major methods for measuring the uncertainty of rough sets.In different knowledge granularity levels,a hierarchical knowledge space chain is proposed based on the attributes in information systems.Some regularities of the changing of rough entropy and fuzziness of a rough set with the knowledge granularity are found to be inconsistent with human cognition.A new method for measuring the fuzziness of rough sets is proposed based on information entropy.The fuzziness measured by the new method is monotonously decreasing with the refining of knowledge granularity in apporiximation spaces.It overcomes the problem of roughness and rough entropy.Finally,the relations of the changing of roughness and fuzziness are analyzed in different knowledge granularities.