【摘要】 粗糙集是用确定的方法处理不确定信息和数据,但它要求属性信息是离散的,而且针对的是完备信息系统。而泛逻辑是研究人工智能领域中的不确定性、不完全性以及模糊性,它针对的信息可以是离散的,也可以是连续的。针对不完备信息系统扩展泛逻辑中的泛等价关系,得到泛容差关系,并对连续或离散的属性取值应用泛容差关系进行分类,代替原来的扩展粗糙集中的容差关系,定义新的相似度的计算方法,进而进行数据填充,最后用实例进行了应用说明。更多还原

【Abstract】 Rough set theory can be used to deal with the imprecise data and information by certain method but its basis is that the attribute’s value must be discrete and the system must be complete.Universal logic can do with the uncertain,incomplete and fuzzy information in artificial intelligence and the data can be discrete or continuous. Use the universal logic to redefine the tolerance relation and use universal tolerance relation to classify the continuous or discrete attribute,we can extend the scope of application of rough set theory and universal logic. This paper makes focus on the new concept of universal tolerance relation and new computation method of similarity between objects and then we can complete the data based on this. At last an example is given to illustrate it.更多还原