基于“逻辑与”算子的双量化多粒度粗糙集模型

Double Quantitative Multi-granulation Rough Set Model Based on “Logical Conjunction” Operator

在多粒度近似空间中,将刻画相对量化信息的变精度粗糙集和描述绝对量化信息的程度粗糙集通过"逻辑与"算子结合起来,建立了基于"逻辑与"算子的双量化多粒度粗糙集模型,并分别从乐观和悲观双量化多粒度粗糙集的角度对模型的一些数学性质进行了讨论。该模型对多粒度近似空间中的相对量化信息和绝对量化信息同时进行了描述,在处理带噪声的数据方面有一定的应用价值,丰富了基于粗糙集理论的知识发现的理论基础。

In this study, the double quantitative multi-granulation rough set model based on logical conjunction operator was proposed in multi-granulat ion approximate space. T he variable precision rough set which is characterized by relative quantitative informat ion and graded rough which describes absolute quantitative inform at ion were conbined to set double quantitative multi-granulat ion rough set model based on logical conjunction operater. Some mathematical properties of the investigated rough set model were researched in the viewpoints of optimistic and pessimistic. The constructed model describes relative quantitative information and absolute quantitative information at the same time in an approximate space. It is useful to process noisy data and provides more abundant theoretical principle fo r knowledge discovery based on rough set theory.