An Algorithm for Granulation Reduction of Multi-granulation Rough Set in Incomplete System

Chinese

您当前的位置：

首页 >

文章列表页 >

An Algorithm for Granulation Reduction of Multi-granulation Rough Set in Incomplete System

更新时间：2026-09-04

- An Algorithm for Granulation Reduction of Multi-granulation Rough Set in Incomplete System
- Vol. 35, Issue 6, Pages: 41-46(2018)
- 作者机构：
- 作者简介：
- 基金信息：
- DOI：
  CLC：
- Published：2018
- 稿件说明：
移动端阅览
不完备系统中的一种多粒度粗糙集粒度约简算法[J]. 微电子学与计算机, 2018, 35(6): 41-46.

An Algorithm for Granulation Reduction of Multi-granulation Rough Set in Incomplete System[J]. 2018, 35(6): 41-46.
不完备系统中的一种多粒度粗糙集粒度约简算法[J]. 微电子学与计算机, 2018, 35(6): 41-46. DOI：

An Algorithm for Granulation Reduction of Multi-granulation Rough Set in Incomplete System[J]. 2018, 35(6): 41-46. DOI：

摘要

本文针对不完备决策信息系统

首先给出粒度上属性值缺失率的定义

结合粒度重要度和粒度上属性值缺失率定义粒度组合重要度

然后以粒度组合重要度为启发函数

设计了新的粒度约简算法

通过调节参数

该算法在保证约简率的同时可以得到属性值缺失率较低的粒度约简结果

最后

实验验证了本文所提算法的有效性.

Abstract

In this paper

for the incomplete information system

the definition of the missing rate of attribute value on granularity is given

and the combination importance of granularity is defined by combining the importance of granularity with the missing rate of attribute value on granularity. Then

a new algorithm of granulation reduction is designed with the combination importance of granularity as the heuristic function

the reduction results of the low missing rate of attribute value can be obtained while ensuring the reduction rate by adjusting the parameters. Finally

the experimental results verify the effectiveness of the proposed algorithms in this paper.

关键词

Keywords

references

Views

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Aerial vehicle detection algorithm based on multi-scale fusion and small-object enhancement

Lightweight countermeasures against Spectre attacks on the branch prediction unit

Research on assembly action recognition based on MSS-YOLO-MPHands fusion architecture

Design of ultra-low power real-time clock circuits

A feature-oriented context understanding and slice analysis network for tuberculosis detection

Related Author

No data

Related Institution

No data

AI问答

Postal code：100079
Tel：（010）53879206 Email：tmw@bjxintong.com.cn
Technical support is provided by Beijing Founder electronics co., LTD 京ICP备09082226号-64 京公网安备11010602201714号
It is recommended to read the content of this site in Chrome&IE9+. Please switch to extreme mode in browser 360.
Cookies We use cookies to help provide and enhance our service and tailor content. By continuing, you agree to the use of cookies.

⁰