On the basis of giving a new type of attribute reduction method, a coupling recognition model is established which combines Rough Sets and neural network closely.
在提出一种属性约简方法的基础上，利用粗糙集和径向基网络的优势，构建了一种耦合模型。
A distributed model of incremental attribute reduction is also presented by decomposing values of decision attribute of positive region and boundary region in non-tolerant decision table.
此外，通过对不相容决策表的正区域的决策值和边界域对原决策表进行分解，得到了一种分布式增量属性约简模型。
Based on the attribute reduction of rough set, from different aspects, this paper sets up indicator screening model based on rough set.
基于粗糙集的属性约简原理，本文从不同的角度建立了基于粗糙集的指标筛选模型。
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