首页 | 本学科首页   官方微博 | 高级检索  
     检索      

面向对象删除的局部邻域粗糙集动态更新算法
引用本文:时俊鹏,张燕兰.面向对象删除的局部邻域粗糙集动态更新算法[J].山东大学学报(理学版),2023,58(5):17-25.
作者姓名:时俊鹏  张燕兰
作者单位: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
基金项目: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。

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

Dynamic updating algorithm of local neighborhood rough sets with the deletion of objects
SHI Junpeng,ZHANG Yanlan.Dynamic updating algorithm of local neighborhood rough sets with the deletion of objects[J].Journal of Shandong University,2023,58(5):17-25.
Authors:SHI Junpeng  ZHANG Yanlan
Institution:1. School of Computer Science, Minnan Normal University, Zhangzhou 363000, Fujian, China;2. Key Laboratory of Data Science and Intelligence Application in Fujian Provincial Universities, Minnan Normal University, Zhangzhou 363000, Fujian, China
Abstract: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.
Keywords:neighborhood information system  local neighborhood rough set  deleting object  approximation set  dynamic updating  
点击此处可从《山东大学学报(理学版)》浏览原始摘要信息
点击此处可从《山东大学学报(理学版)》下载免费的PDF全文
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号