CAJ | 학술논문

模糊粗糙集的知识约简是模糊粗糙集理论的核心内容之一，从增量式的数据、海量数据或动态数据中挖掘出人们感兴趣的知识，是数据挖掘研究的一个重点，也是一个难点。首先，给出模糊粗糙集的属性重要度的定义及属性约简的定义；其次，从F-粗糙集及并行约简出发，并结合模糊粗糙集的属性重要度，提出了F-模糊粗糙集及其约简，为增量式或动态模糊决策表的属性约简提供了一种有效的方法；最后，通过实例验证了F-模糊粗糙集及其约简的可行性。
모호조조집적지식약간시모호조조집이론적핵심내용지일，종증량식적수거、해량수거혹동태수거중알굴출인문감흥취적지식，시수거알굴연구적일개중점，야시일개난점。수선，급출모호조조집적속성중요도적정의급속성약간적정의；기차，종F-조조집급병행약간출발，병결합모호조조집적속성중요도，제출료F-모호조조집급기약간，위증량식혹동태모호결책표적속성약간제공료일충유효적방법；최후，통과실례험증료F-모호조조집급기약간적가행성。
The fuzzy-rough attribute reduction is one of the important topics in fuzzy-rough set theory. It is a focal difficult point to mine interesting knowledge from incremental data, mass data and dynamic data. It was defined the fuzzy rough set′s attribute significance and the concept of attribute reduction; The F-fuzzy rough sets and its reducts were proposed then based on the attribute significance of fuzzy rough sets, F-rough sets and its parallel reducts. The F-fuzzy rough sets′s reducts were showed to be an effective methodology for attribute reduction on incremental and dynamic fuzzy decision table;Furthermore the feasibilities of F-fuzzy rough sets and its parallel reducts were confirmed by examples.