多粒度近似空间中基于“逻辑或”算子的双量化粗糙集模型  

Double Quantitative Rough Set Model Based on Logical Disjunct Operation in Multi-Granulation Approximate Space

作　　者：陈华峰 沈玉玲 瞿先平 

机构地区：[1]重庆电讯职业学院,基础部,重庆 [2]重庆理工大学,计算机科学与工程学院,重庆

出　　处：《运筹与模糊学》2017年第4期152-162,共11页Operations Research and Fuzziology

基　　金：重庆市科委基础学科与前沿技术研究基金(No.cstc2015jcyjBX0127);重庆市教委科学技术研究基金(Nos.KJ1500922,KJ1605201)支助。

摘　　要：变精度粗糙集和程度粗糙集都是在单粒度近似空间中,基于不可分辨关系的扩展粗糙集模型。从信息量化角度来说,变精度粗糙集描述了近似空间中的相对量化信息,程度粗糙集则用于对绝对量化信息的表示中,而多粒度近似空间作为一种广义的近似空间,是对经典近似空间的自然扩张。为了在多粒度近似空间中研究同时具有信息的相对量化和绝对量化特征的粗糙集模型,本文通过“逻辑或”算子将变精度粗糙集和程度粗糙集在多粒度近似空间中结合起来,建立了“逻辑或”双量化多粒度粗糙集模型。并对该模型的粗糙集区域,以及所具有的一些基本数学性质进行了深入的讨论,为多粒度近似空间中基于粗糙集理论的知识发现,提供了新的研究方法。Both the variable precision rough set and graded rough set are the generalized rough set models based on indiscernibility relation in single granulation approximate space. In the viewpoint of information quantitative, the variable precision rough set describes relative quantitative infor-mation, while graded rough set is used to represent the absolute quantitative information in ap-proximate space. The multi-granulation approximate space as a generalized approximate space is a natural expansion of classical approximation space. In order to study the rough set model that include characteristics of variable precision rough set and graded rough set. We combine them into a double-quantitative multi-granulation rough set model based on logical disjunct operation. Furthermore, the rough set regions and some basic mathematical properties of the proposed model are discussed in detail. This research provides a novel approach to knowledge discovery in multi-granulation approximate space based on rough set theory.

关 键 词：多粒度近似空间 逻辑或 变精度粗糙集 程度粗糙集 双量化 

分 类 号：TP1[自动化与计算机技术—控制理论与控制工程]