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Rough set model under a limited asymmetric similarity relation and an approach for incremental updating approximations

机译:有限不对称相似关系下的粗糙集模型及增量更新逼近方法

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摘要

The rough set model under the asymmetric similarity relation is an extension of classical rough set model under equivalence relation, by which incomplete information systems can be dealt with effectively. In this paper, a new extension model of rough set under a kind of limited asymmetric similarity relation is proposed firstly, and then by providing four theorems on incremental updating approximations and their proofs, an approach for incremental updating approximations is presented under the limited asymmetric similarity relation when the attribute set is dynamically changing in incomplete information systems. Finally, An illustrative example is given to verify the validity of the proposed method. Moreover, it may be used to support dynamic knowledge discovery.
机译:非对称相似关系下的粗糙集模型是等价关系下经典粗糙集模型的扩展,可以有效地处理不完整的信息系统。本文首先提出了一种在有限非对称相似关系下的粗糙集扩展模型,然后通过提供四个关于增量更新近似的定理及其证明,提出了一种在有限非对称相似度下的增量更新近似的方法。属性集在不完整信息系统中动态变化时的关系。最后,给出一个说明性的例子来验证所提方法的有效性。此外,它可以用于支持动态知识发现。

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