基于双重粒化准则的邻域多粒度粗糙集模型  

Neighborhood multi-granulation rough set model based on double granulate criterion

作　　者：徐怡[1,2] 杨宏健[1,2] 纪霞[1,2] 

机构地区：[1]安徽大学计算机科学与技术学院,合肥230601 [2]安徽大学计算智能与信号处理教育部重点实验室,合肥230601

出　　处：《控制与决策》2015年第8期1469-1478,共10页Control and Decision

基　　金：国家自然科学基金项目(61402005);安徽省自然科学基金项目(1308085QF114);安徽省高等学校省级自然科学基金项目(KJ2013A015;KJ2011Z020);安徽大学计算智能与信号处理教育部重点实验室课题项目

摘　　要：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 with the heterogeneous data including categorical attributes and numerical attributes from the multi-granularity and multi-level perspective effectively, double granulate criterion is built on different attribute sets sequence and different neighborhood radii. The neighborhood multi-granulation rough set model based on the double granulate criterion is proposed. Several relevant properties of the model are given, and an attribute reduction algorithm of the proposed model is presented. The reduction result can choose the appropriate attribute set and neighborhood radius flexibly according to the need of practical problems. The effectiveness of the proposed model and algorithm is verified by some examples.

关 键 词：粗糙集 多粒度 邻域关系 双重粒化准则 属性约简 

分 类 号：TP311[自动化与计算机技术—计算机软件与理论]