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《山东大学学报(理学版)》 ›› 2020, Vol. 55 ›› Issue (1): 51-61.doi: 10.6040/j.issn.1671-9352.1.2019.167

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多粒度粗糙集近似集的增量方法

张海洋1,马周明1,2*,于佩秋1,林梦雷1,李进金1   

  1. 1.闽南师范大学数学与统计学院, 福建 漳州 363000;2.数字福建气象大数据研究所, 福建 漳州 363000
  • 发布日期:2020-01-10
  • 作者简介:张海洋(1995— ),男, 硕士研究生,研究方向为粗糙集. E-mail:1913570847@qq.com*通信作者简介:马周明(1979— ),男, 博士,副教授,研究方向为人工智能、粒计算和粗糙集. E-mail:44842802@qq.com
  • 基金资助:
    国家自然科学基金资助项目(A011404,61573127,61672272,61603173,11701258);福建省自然科学基金资助项目(2017J01507,2019J01748)

Incremental method for approximating sets of multi-granularity rough sets

ZHANG Hai-yang1, MA Zhou-ming1,2*, YU Pei-qiu1, LIN Meng-lei1, LI Jin-jin1   

  1. 1. School of Mathematics and Statistics, Minnan Normal University, Zhangzhou 363000, Fujian, China;
    2. Digital Fujian Meteorological Big Data Research Institute, Zhangzhou 363000, Fujian, China
  • Published:2020-01-10

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摘要： 利用正确分类率来考虑属性论域同时变化时基于向量矩阵的经典多粒度粗糙集上下近似集的动态近似更新。首先讨论了论域缩小属性增加时,多粒度粗糙集的上下近似算子一些性质的改变,并给出了基于向量矩阵的近似集更新方法;其次讨论了论域缩小属性减少时,相应算子性质的变化,并给出了基于向量矩阵的近似集更新方法。新方法有效地缩小了经典多粒度粗糙集近似集更新时的搜索区域。

关键词: 增量计算, 近似集更新, 多粒度粗糙集, 向量矩阵

Abstract: Dynamic updating the upper and lower approximations in multi-granulation rough sets based on column matrix mainly use the relative correct classification rate to consider the varying attribute values and varying universe simultaneously. First, we discuss some properties of upper and lower approximation operators of multi-granulation rough sets while the universe decreasing and adding attributes, and give an updating method for approximations based on column matrix. Second, we discuss some properties of approximation operators while the universe decreasing and adding attributes, and give an updating method based on column matrix. The methods we proposed effectively shrink the searching region when updating the approximations of the multi-granulation rough sets.

Key words: incremental computing, updating approximation, multi-granulation rough set, column matrix

中图分类号: 

  • TP18
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