中南大学学报（自然科学版）2009，Vol.40Issue(5)：1360-1366,7.
广义相似关系下的不完备信息系统粗糙集模型
Rough set model based on general similarity relation in incomplete information systems
摘要
Abstract
In order to extract reasonable rule-based knowledge from information systems with hybrid data and incomplete data, a new rough set model based on general similarity relation in incomplete information systems was proposed. The procedures were as follows: Firstly, general similarity relations were defined for the situation of hybrid data and different kinds of incomplete data in information systems. Secondly, two kinds of attribute reduction methods and rule-based knowledge extraction methods were investigated, which were built upon the concepts of upper and lower approximations with upper and lower general similarity partitions. Lastly, the extended rough set model was proved theoretically, and a numerical example reveals the validity and advantage of the proposed model.关键词
广义相似关系/不完备信息系统/上近似/下近似/粗糙集Key words
general similarity relation/ incomplete information system/ upper approximation/ lower approximation/ rough set theory分类
信息技术与安全科学引用本文复制引用
谭旭,陈英武,王桢珍..广义相似关系下的不完备信息系统粗糙集模型[J].中南大学学报（自然科学版）,2009,40(5):1360-1366,7.基金项目
国家自然科学基金资助项目(70272002) （70272002）
