计算机科学 ›› 2010, Vol. 37 ›› Issue (9): 225-228.
• 人工智能 • 上一篇 下一篇
解滨，李磊军，米据生
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XIE Bin,LI Lei-jun,MI Ju-sheng
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摘要： 粗糙集的不确定性与其所在近似空间知识粒度的大小密切相关。提出了近似空间中集合的相对知识粒度的概念。基于相对知识粒度的粗糙集的粗糙性度量既刻画了近似空间对粗糙集不确定性的影响，又去除了负域的干扰。从边界嫡的角度提出了一种粗糙集的模糊性度量。随着近似空间知识粒的细分，粗糙集的粗糙度与模糊度均单调递减。
关键词: 粗糙集，知识粒度，粗糙度，模糊度，不确定性
Abstract: Uncertainty of rough sets has close relatives with the knowledge granularities of the approximation space. A concept of relative knowledge granularities was proposed. The roughness of a rough set based on relative knowledge granularities not only reflects the action of the approximation space, but also gets rid of the effect of the negative region of the rough set. A new kind of fuzziness of rough sets based on boundary entropy was designed. Both of the roughness and fuzziness are monotonously decreasing with the refining of knowledge granularities in approximation spaces.
Key words: Rough sets,Knowledge granularities,Roughness,Fuzziness,Uncertainty
解滨，李磊军，米据生. 基于知识粒度的粗糙集的不确定性度量[J]. 计算机科学, 2010, 37(9): 225-228. https://doi.org/
XIE Bin,LI Lei-jun,MI Ju-sheng. Uncertainty Measures of Rough Sets Based on Knowledge Granularities[J]. Computer Science, 2010, 37(9): 225-228. https://doi.org/
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