面向对象删除的局部邻域粗糙集动态更新算法  

Dynamic updating algorithm of local neighborhood rough sets with the deletion of objects

作　　者：时俊鹏 张燕兰 SHI Junpeng;ZHANG Yanlan(School of Computer Science,Minnan Normal University,Zhangzhou 363000,Fujian,China;Key Laboratory of Data Science and Intelligence Application in Fujian Provincial Universities,Minnan Normal University,Zhangzhou 363000,Fujian,China)

机构地区：[1]闽南师范大学计算机学院,福建漳州363000 [2]数据科学与智能应用福建省高校重点实验室,福建漳州363000

出　　处：《山东大学学报（理学版）》2023年第5期17-25,共9页Journal of Shandong University(Natural Science)

基　　金：国家自然科学基金资助项目(11701258,11871259);福建省自然科学基金资助项目(2022J01912,2020J01801,2020J02043,2019J01749);福建省高校杰出青年科研人才培养计划。

摘　　要：为了有效地计算动态数值型数据的近似算子,提出了一种局部邻域粗糙集模型的动态更新算法,分析对象集减少时局部近似集的更新公式,设计获取局部近似集的动态算法。动态更新算法充分利用已有知识,避免了大量重复计算。为了验证算法的有效性,使用来自UCI的6组数据集进行了对比实验。A dynamic updating algorithm of the local neighborhood rough set model is proposed effectively to obtain the approximation operators of dynamic numerical data.We analyze the updating formula of the local approximation set when the object set decreases and design a dynamic algorithm to obtain the local neighborhood approximation sets.The dynamic updating algorithm can make full use of existing knowledge and avoid a considerable part of repeated calculations.To verify the effectiveness of the algorithm,comparative experiments are conducted using six datasets from UCI.

关 键 词：邻域信息系统 局部邻域粗糙集 对象删除 近似集 动态更新 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]