摘要
为了解决邻域粗糙模糊集模型的增量式计算问题,提出一种矩阵策略的邻域粗糙模糊集动态更新算法。提出一种基于矩阵方法的邻域粗糙模糊集模型,通过邻域关系矩阵和模糊决策对角阵的矩阵运算,实现了邻域粗糙模糊近似集的矩阵表达;当信息系统增加和删除对象时,增量式更新邻域关系矩阵和模糊决策对角阵的结果,并利用更新后矩阵的运算实现了邻域粗糙模糊近似集的动态更新,因此减少了不必要的计算且提升了性能;利用所提出的增量式更新机制设计了邻域粗糙模糊集的动态更新算法。在UCI数据集上的实验结果表明,该动态算法的运行效率明显高于静态算法和同类型动态算法。
To solve the incremental computation problem of neighborhood rough fuzzy set models,a matrix strategy-based dynamic update algorithm for neighborhood rough fuzzy sets is proposed.A neighborhood rough fuzzy set model is introduced,utilizing a matrix method.Through matrix operations of the neighborhood relation matrix and fuzzy decision diagonal matrix,the matrix expression of the neighborhood rough fuzzy approximation set is achieved.As the information system adds and removes objects,the results of the neighborhood relation matrix and fuzzy decision diagonal matrix are incrementally updated.This dynamic updating of the neighborhood rough fuzzy approximation set is achieved by operating on the revised matrix,thereby reducing unnecessary calculations and improving performance.A dynamic update algorithm for neighborhood rough fuzzy sets is built on this incremental update mechanism.The experimental results on the UCI dataset show that this dynamic algorithm’s operational efficiency is significantly higher than that of static algorithms and dynamic algorithms of the same type.
作者
何柳
周雯
HE Liu;ZHOU Wen(School of Information Engineering,Wuhan Business University,Wuhan 430056,China;Materials Science and Engineering College,Wuhan University of Science and Technology,Wuhan 430081,China)
出处
《计算机工程与设计》
北大核心
2025年第8期2200-2210,共11页
Computer Engineering and Design
基金
教育部产学合作协同育人基金项目(230702036245313)
湖北省高校省级教学改革研究课题基金项目(2020691)。
关键词
粗糙集
模糊粗糙集
邻域粗糙模糊集
模糊决策
动态更新
矩阵
增量式
rough set
fuzzy rough set
neighborhood rough fuzzy sets
fuzzy decision
dynamic updates
matrix
incremental
