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中文摘要：
将粒计算融入到概念格研究中，结合相似度模型和概念格结构信息，提出一种基于粒计算的概念格拓展模型，其有助于扩展经典概念的内涵和外延，也有助于压缩概念的规模．该模型是概念格和粒计算融合研究的一次有益探索和尝试，同时对概念格拓展也不失为一种有效手段．
英文摘要：
By introducing granular computing into concept lattice, and integrating similarity measure model and structure information of concept lattice, the paper proposes an expanded concept lattice model based on granular computing. It can help to expand intent and extent of classical concept, and also can effectively reduce the scale of concepts to some extent. The model is not only a useful attempt and exploration for the fusion of these two theories, but also an effective means of expanding the classical concept lattice.
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同项目期刊论文
Knowledge Granulation, Rough Entropy and Information Entropy in Interval-valued Information Systems.
Best basis-based wavelet packet entropy feature extraction and hierarchical EEG classification for e
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