平均近似精度的性质和应用  

Properties and Applications of Average Approximation Accuracy

作　　者：张夏苇[1] 孔庆钊[2] ZHANG Xiawei;KONG Qingzhao(School of Mathematics and Statistics,Xiamen University of Technology,Xiamen,Fujian 361024,China;College of Science,Jimei University,Xiamen,Fujian 361021,China)

机构地区：[1]厦门理工学院数学与统计学院,福建厦门361024 [2]集美大学理学院,福建厦门361021

出　　处：《计算机科学》2024年第S02期616-620,共5页Computer Science

基　　金：福建省自然科学基金(2020J01707)。

摘　　要：平均近似精度是粗糙集理论中新近提出的一个重要概念。首先分析平均近似精度的数学结构,给出平均近似精度一种新的解释;然后重点讨论平均近似精度的若干重要性质,相比传统方法,其能更有效地刻画粗糙集模型知识表示的能力;最后,探讨平均近似精度在不完备信息表和特征选择两方面的应用。这些研究成果丰富了粗糙集理论的内容,扩展了粗糙集理论在实际问题中的应用。Average approximation accuracy is an important concept in rough set theory,which has only been proposed in recent years.In this paper,the mathematical structure of average approximation accuracy is first analyzed,and another new explanation for average approximation accuracy is provided.Then,we focus on discussing several important properties of average approximation accuracy,and find that average approximation accuracy can characterize the knowledge representation ability of rough set models more effectively than traditional methods.Finally,the applications of average approximation accuracy in incomplete information tables and feature selection are discussed,respectively.These research achievements will enrich the content of rough set theory and expand its application in practical problems.

关 键 词：粗糙集 近似精度 属性约简 不完备信息表 

分 类 号：TP182[自动化与计算机技术—控制理论与控制工程]