CAJ | 학술논문

粗糙集理论研究的核心内容之一是属性重要性的度量和属性约简。经典的粗糙集模型基于等价关系，适合于处理离散属性值。模糊粗糙集理论将模糊集和粗糙集理论结合起来，将等价关系扩展为模糊关系，可处理模糊属性值。分析了已有广泛运用的模糊决策表的属性约简算法FRAR存在的三个问题，提出了一种新的约简算法，较好地克服了原算法的问题，能处理规模较大的模糊决策表。
조조집이론연구적핵심내용지일시속성중요성적도량화속성약간。경전적조조집모형기우등개관계，괄합우처리리산속성치。모호조조집이론장모호집화조조집이론결합기래，장등개관계확전위모호관계，가처리모호속성치。분석료이유엄범운용적모호결책표적속성약간산법FRAR존재적삼개문제，제출료일충신적약간산법，교호지극복료원산법적문제，능처리규모교대적모호결책표。
The attribute importance measure and attribute reduction is one of the core content of rough sets theory. The classical rough set model based on equivalence relation, is suitable for dealing with discrete attribute values. Fuzzy-rough set theory, com-bining fuzzy set and rough set theory, extending equivalence relation to fuzzy relation, can deal with fuzzy attribute values. By analyzing three problems of FRAR which is a fuzzy decision table attribute reduction algorithm having extensive use, this paper proposes a new reduction algorithm which has better overcome the problem, can handle larger fuzzy decision table.