Possible Coverings in Incomplete Information Tables with Similarity of Values
Possible Coverings in Incomplete Information Tables with Similarity of Values
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DOI：
10.1007/978-3-030-87334-9_7
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发表时间：
2021
期刊：
影响因子：
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通讯作者：
M. Nakata;Norio Saito;H. Sakai;Takeshi Fujiwara
中科院分区：
文献类型：
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作者：
M. Nakata;Norio Saito;H. Sakai;Takeshi Fujiwara
粗糙集是用具有相似性的不完全信息表中的可能覆盖来描述的。在不完全信息表中导出了许多可能的覆盖。由于计算的复杂性，这似乎会造成困难，但事实并非如此，因为可能覆盖族具有格结构。组成粗糙集的四个近似是通过使用两个覆盖来导出的：最小和最大可能的覆盖是从最小和最大可能的不相容关系导出的，这些不相容关系等于来自可能表的那些不相容关系的交集和并集。近似值等于使用最小和最大可能不可分辨类导出的近似值。
Rough sets are described by an approach using possible coverings in an incomplete information table with similarity of values. Lots of possible coverings are derived in an incomplete information table. This seems to cause difficulty due to computational complexity, but it is not, because the family of possible coverings has a lattice structure. Four approximations that make up a rough set are derived by using only two coverings: the minimum and maximum possible ones which are derived from the minimum and the maximum possible indiscernibility relations that are equal to the intersection and the union of those from possible tables. The approximations are equal to those derived using the minimum and the maximum possibly indiscernible classes.