摘要
针对具有动态特征的信息系统,在S-粗集属性迁移理论基础上,给出了S-粗集上的区分矩阵,提出了一种基于S-粗集区分矩阵的属性约简算法。该算法弥补了Z.Pawlak粗集理论对于动态系统知识发现的局限,通过属性迁移对不完备的信息系统进行动态扩展,约简后生成的规则简单准确。本文的算法具有理论与应用的一般性、广泛性,对于现代战场中的ARM识别,更显示出了极强的优越性。
To the information system which possesses dynamic characteristic, the discernable matrix of S-rough set is put forward based on S-rough set attribute transfer theory, and a new attribute reduction algorithm is presented based on discernable matrix of S-rough set. The algorithm makes up the localization of Z. Pawlak rough set theory in disposing dynamic system knowledge discovery, the incomplete information system is extended by attribute transfer, and reduction rules are simple and exact. The algorithm has uni- versality in theory and application, and it shows exceeding advantage in the ARM identification.
出处
《传感技术学报》
CAS
CSCD
北大核心
2009年第4期480-483,共4页
Chinese Journal of Sensors and Actuators
基金
国家自然科学基金资助(60773209)
陕西省自然科学基金资助(2006F18)
关键词
S-粗集
属性迁移
区分矩阵
目标识别
ARM
S-rough set
attribute transfer
discernable matrix
target identification
ARM
