第一个GrC模型-邻域系统最一般的粗糙集模型

Xibei Yang, Xinzhe Li, T. Lin
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引用次数: 13

摘要

从形式GrC模型的角度重新审视邻域系统(NS)。NS形式化了古老的直觉——无穷小,它导致了微积分、拓扑学和非标准分析的发明。本文证明Ziarko变精度模型可以用NS表示。结合先前已知的结果(NS包括拓扑、二元关系(二元邻域系统)和覆盖作为特殊情况),NS是最通用的粗糙集模型。引入了一个新的运算“and”,生成拓扑的基;我们称之为知识库。基于这种知识库的近似可以理解为学习。这与传统的粗糙集近似不同。
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First GrC model - Neighborhood Systems the most general rough set models
Neighborhood System(NS) is revisited from the view of Formal GrC Model. NS formalize the ancient intuition, infinitesimals, which led to the invention of calculus, topology and non-standard analysis. In this paper, we show that Ziarko's variable precision model can be expressed by NS. Together with previously known results (NS includes topology, binary relation(binary neighborhood system) and covering as special cases), NS is the most general rough set model. A new operation “and” is introduced that generates a base of a topology; we will call it knowledge base. The approximations based on such knowledge base can be interpreted as learning. This is different from traditional rough set approximations.
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