基于矩阵的可变粒度变精度邻域粗糙集近似集更新方法  

Matrix-based Approaches for Updating Approximations in Variable Granulation Variable Precision Neighborhood Multigranulation Rough Sets While Neighborhood Classes Decreasing

作　　者：郑文彬 李进金 张燕兰 许晴媛 ZHENG Wen-bin;LI Jin-jin;ZHANG Yan-lan;XU Qing-yuan(School of Computer Science,Minnan Normal University,Zhangzhou 363000,China;Key Laboratory of Data Science and Intelligence Application,Zhangzhou 363000,China;School of Mathematics and Statistics,Minnan Normal University,Zhangzhou 363000,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 [3]闽南师范大学数学与统计学院,福建漳州363000

出　　处：《模糊系统与数学》2022年第1期97-109,共13页Fuzzy Systems and Mathematics

基　　金：国家自然科学基金资助项目(61379021;11871259);福建省自然科学基金资助项目(2019J01748)。

摘　　要：邻域粗糙集可以同时处理名义与数值属性,多粒度粗糙集提供多个粒度视角下的目标概念近似,变精度粗糙集使得近似集计算不再局限于完全包含。本文首先提出了一种同时具有以上三种粗糙集模型长处并且粒度可变的变精度多粒度邻域粗糙集模型,并设计基于矩阵的近似集计算与更新方法:首先提出静态计算近似集的矩阵算法,继而考虑在邻域粒变小时,基于静态计算算法对近似集进行更新,提出一种邻域粒变小时近似集更新的矩阵算法,最后通过UCI公开数据集实验验证了计算与更新算法的有效性。Neighborhood rough sets can handle category and numerical attributes simultaneously. Multigranulation rough sets provide approximations of target concepts from multiple granulation perspectives. Variable precision rough sets make the calculation of approximate sets no longer limited to complete inclusion. This paper first proposes a Variable Granulation Variable Precision Neighborhood Multigranulation Rough Sets(VG-VP-NMGRS) with the advantages of the above three rough set models and variable granulation. And propose VG-VP-NMGRS approximation set calculating and updating method of matrix: firstly, a relative matrix-based algorithm for calculating approximations in VG-VP-NMGRS is proposed, and then when the neighborhood classes are decreasing, the incremental algorithm for updating approximations is proposed based on the static calculating algorithm. Finally, the validity of the static and incremental algorithms is verified by UCI data set experiments.

关 键 词：动态计算 近似集更新 可变粒度可变精度邻域多粒度粗糙集 矩阵算法 

分 类 号：O159[理学—数学]