为了从多粒度、多层次的角度有效处理名义型属性和数值型属性并存的混合数据,首先基于不同的属性集序列和不同的邻域半径构建双重粒化准则,建立基于双重粒化准则的邻域多粒度粗糙集模型;然后给出该模型的相关性质,提出该模型下的属性约简算法,约简结果可以根据实际问题的需要灵活选择合适的属性集和邻域半径.实例分析验证了所提出模型和算法的有效性. In order to deal effectively with mixed data with both nominal and numerical attributes coexisting efficiently from multi-granularity and multilevel perspectives, we first construct a dual granularity criterion based on different attribute set sequences and different neighborhood radii, Domain multi-granularity rough set model. Then the related properties of the model are given and the attribute reduction algorithm is proposed. The reduction result can select the appropriate attribute set and neighborhood radius flexibly according to the actual problem. The effectiveness of the proposed model and algorithm.