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DOI:
Journal of Software:2001.12(3):415-419

Rough逻辑及其在数据约简中的应用
刘清,刘少辉,郑非
(南昌大学 计算机科学与工程系,江西 南昌 330029)
Rough Logic and Its Applications in Data Reduction
LIU Qing,LIU Shao-hui,ZHENG Fei
()
Abstract
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Received:October 22, 1999    Revised:January 21, 2000
> 中文摘要: 讨论了被定义在邻域值决策表上的Rough逻辑及其公式的真值,它在数据约简中的应用比Pawlak定义的决策表上的决策逻辑更加广泛.目前常用的数据约简方法有Pawlak的数据分析和Skowron的分明矩阵法.前者是非形式的,不易机械化;而后者虽说直观、易理解,但还要求生成一个分明矩阵的中间环节,从而造成时空上的不必要的开销.采取一边从邻域值决策表关于属性值邻域是分明的属性并构成邻域分明合取范式,一边做这种逻辑公式的等价变换直接得到邻域值决策表的诸多约简.由于不用生成分明矩阵的中间环节,这样便节省了空间和时间,
Abstract:The rough logic defined on neighbor-valued decision tables and its truth values of the formulas are discussed in this paper. It is more general than the decision logic defined by Pawlak in the applications of data reduction. At present, the methods used are often Pawlak's data analysis and Skowron's discernible matrix methods. The former is informal, no ease mechanization. The latter is intuitive, easy to understand, but it requires to generate a medial link of discernible matrix, to make unnecessary expenses on time and space. Therefore, in the paper, one side extracts the attributes of attribute neighbor-valued discernible from the neighbor-valued decision table and discernible Conjunctive Normal Form is constructed. The other side simpli