基于多重阈值的变精度多粒度粗糙集模型  

A variable precision multi-granulation rough set model based on multiple thresholds

作　　者：徐怡[1,2] 李策[2] 

机构地区：[1]安徽大学计算智能与信号处理教育部重点实验室,安徽合肥230039 [2]安徽大学计算机科学与技术学院,安徽合肥230601

出　　处：《计算机工程与科学》2016年第8期1727-1734,共8页Computer Engineering & Science

基　　金：国家自然科学基金(61402005);安徽省自然科学基金(1308085QF114);安徽省高等学校省级自然科学基金(KJ2013A015);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：传统变精度多粒度粗糙集模型是基于单一变精度阈值的,而多粒度粗糙集模型是从多角度和多层次处理数据,数据往往是多源的或者是分布式的,其噪音数据的含量也各不相同。因此,不同知识粒度层次所应具有的变精度阈值也不相同,这使得现有的模型难以适应多粒度环境。为克服上述缺点,提出了基于多重阈值的变精度多粒度粗糙集模型,该模型使得不同知识粒度层次的变精度阈值可独立调整,更符合多粒度粗糙集模型的数据特征。该模型更好地结合了多粒度粗糙集模型和变精度粗糙集模型,可从多角度分析解决问题又兼具更灵活的容错能力。Traditional variable precision multi-granulation rough sets are based on a single threshold while the multi-granulation rough set model processes data from multiple perspectives and multi-level. Data acquisition methods of different knowledge granularity are not the same and the noise data is also different. So the variable precision thresholds of different knowledge granularity levels should be different, which makes the traditional model incapable of adapting to the multiranulation environment. In order to solve this problem, we propose a variable precision multi-granulation rough set model based on multiple thresholds. The model makes the variable precision threshold of different levels of knowledge granularity can be adjusted independently and it is more consistent with the data features of the multigranulation rough set model. The model combines the multi-granulation rough set model and the variable precision rough set model with a more suitable method, which can solve the problem from multiple perspectives and has more flexible fault tolerance ability.

关 键 词：多粒度粗糙集模型 变精度粗糙集模型 多重阈值 知识粒度 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]