FT-粗糙集模型的一些性质
Some Properties of the FT-Rough Set Model
张纪平 1周缪娟 2李进金2
作者信息
- 1. 泉州师范学院 数学与计算机科学学院,福建 泉州 362000
- 2. 闽南师范大学 数学与统计学院,福建 漳州 363000
- 折叠
摘要
T-粗糙集是Pawlak粗糙集理论发展过程中的一个重要模型,已成功应用于数据挖掘等诸多领域.FT-粗糙集模型能够在保持数据的完整性下处理连续型数据,是对仅能处理离散型数据的T-粗糙集模型上的发展.文章引入模糊近似空间(X,Y,T一对模糊集的弱逆和强逆定义,用量化方法研究FT-粗糙集的一些性质,得到模糊技能映射在析取模型、合取模型下分别生成的知识结构;用量化方法与矩阵表示探究FT-粗糙集模糊集值映射在并、交运算下的性质.
Abstract
T-rough set is an important model in the development of Pawlak rough set theory,and has been successfully applied to data mining and many other fields.The FT-rough set model can process continu-ous data while maintaining data integrity,which is a development of the T-rough set model that can only handle discrete data.In this study,we introduced the weak inverse and strong inverse definitions of a pair of fuzzy sets in a fuzzy approximation space,studied some properties of FT-rough sets by quantification method,and obtained the knowledge structure generated by fuzzy skill mapping under the disjunctive model and the conjunction model,and explored the properties of FT-rough set fuzzy set value mapping under union and intersection operations by quantization method and matrix representation.
关键词
FT-粗糙集/模糊近似空间/下逆和上逆/弱逆和强逆Key words
FT-rough/blur approximate space/upper inverse and lower inverse/weak inverse and strong inverse引用本文复制引用
基金项目
国家自然科学基金(12271191)
福建省自然科学基金(2023J05175)
福建省教育科学规划课题(十四五)(FJJKBK23-064)
出版年
2024
NETL
NSTL
万方数据