globalchange  > 气候变化事实与影响
CSCD记录号: CSCD:5979915
论文题名:
基于聚类的轮廓数据质量监控方法研究
其他题名: Profile Monitor Based on Clustering Method
作者: 聂斌; 姚雪海; 李京亚
刊名: 运筹与管理
ISSN: 1007-3221
出版年: 2017
卷: 26, 期:4, 页码:444-454
语种: 中文
中文关键词: 变点识别 ; 聚类分析 ; 小波变换 ; 轮廓线 ; 统计过程控制
英文关键词: change-point detection ; cluster analysis ; wavelet transform ; profile ; SPC
WOS学科分类: ECONOMICS
WOS研究方向: Business & Economics
中文摘要: 轮廓线的变点识别是质量管理的研究热点之一,当前研究多以轮廓整体变化为识别对象,而对局部变化问题研究相对较少,且更少有在发现变异时间的同时能够寻找到变化区域在个体轮廓曲线上位置的系统方法。本文针对轮廓线局部变化识别问题,提出基于小波变换和聚类分析的方法。通过仿真性能评价,并与现有方法进行比较,结果显示本方法能够在更小的差异度检测出变化并准确定位变化区域。在文章的末尾,本文采用了一个实例对该方法的效果进行验证。
英文摘要: Change-point detection of profiles has been a hot topic in quality management. Most of the literatures focus on the global change detection while research on local change problem is relatively few, and the ones that find change time as well as change area are extremely less. To solve local change problem,our paper proposes a method based on wavelet transform and cluster method. In this paper, we do a performance evaluation using Matlab and compare its result with WANOVA method. It shows that our method can detect change-point and locate change area under smaller difference between profiles.
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/153347
Appears in Collections:气候变化事实与影响

Files in This Item:

There are no files associated with this item.


作者单位: 天津大学管理与经济学部, 天津 300072, 中国

Recommended Citation:
聂斌,姚雪海,李京亚. 基于聚类的轮廓数据质量监控方法研究[J]. 运筹与管理,2017-01-01,26(4):444-454
Service
Recommend this item
Sava as my favorate item
Show this item's statistics
Export Endnote File
Google Scholar
Similar articles in Google Scholar
[聂斌]'s Articles
[姚雪海]'s Articles
[李京亚]'s Articles
百度学术
Similar articles in Baidu Scholar
[聂斌]'s Articles
[姚雪海]'s Articles
[李京亚]'s Articles
CSDL cross search
Similar articles in CSDL Cross Search
[聂斌]‘s Articles
[姚雪海]‘s Articles
[李京亚]‘s Articles
Related Copyright Policies
Null
收藏/分享
所有评论 (0)
暂无评论
 

Items in IR are protected by copyright, with all rights reserved, unless otherwise indicated.