中国科学院国家天文台机构知识库
Advanced  
NAOC Open IR  > 应用天文研究部  > 期刊论文
题名:
Automated clustering algorithms for classification of astronomical objects
作者: Zhang, Y; Zhao You(赵有)
关键词: methods : data analysis ; methods : statistical ; astronomical data bases : miscellaneous ; catalogs
刊名: ASTRONOMY & ASTROPHYSICS
发表日期: 2004-08-01
DOI: 10.1051/0004-6361:20040141
卷: 422, 期:3, 页:1113-1121
收录类别: SCI
英文摘要: Data mining is an important and challenging problem for the efficient analysis of large astronomical databases and will become even more important with the development of the Global Virtual Observatory. In this study, learning vector quantization (LVQ), single-layer perceptron (SLP) and support vector machines (SVM) were used for multi-wavelength data classification. A feature selection technique was used to evaluate the significance of the considered features for the results of classification. We conclude that in the situation of fewer features, LVQ and SLP show better performance. In contrast, SVM shows better performance when considering more features. The focus of the automatic classification is on the development of an efficient feature-based classifier. The classifiers trained by these methods can be used to preselect AGN candidates.
语种: 英语
WOS记录号: WOS:000223659500037
Citation statistics:
内容类型: 期刊论文
URI标识: http://ir.bao.ac.cn/handle/114a11/8113
Appears in Collections:应用天文研究部_期刊论文

Files in This Item:

There are no files associated with this item.


作者单位: Chinese Acad Sci, Natl Astron Observ, Beijing 100012, Peoples R China

Recommended Citation:
Zhang, Y,Zhao, Y. Automated clustering algorithms for classification of astronomical objects[J]. ASTRONOMY & ASTROPHYSICS,2004,422(3):1113-1121.
Service
Recommend this item
Sava as my favorate item
Show this item's statistics
Export Endnote File
Google Scholar
Similar articles in Google Scholar
[Zhang, Y]'s Articles
[Zhao, Y]'s Articles
CSDL cross search
Similar articles in CSDL Cross Search
[Zhang, Y]‘s Articles
[Zhao, Y]‘s Articles
Related Copyright Policies
Null
Social Bookmarking
Add to CiteULike Add to Connotea Add to Del.icio.us Add to Digg Add to Reddit
所有评论 (0)
暂无评论
 
评注功能仅针对注册用户开放,请您登录
您对该条目有什么异议,请填写以下表单,管理员会尽快联系您。
内 容:
Email:  *
单位:
验证码:   刷新
您在IR的使用过程中有什么好的想法或者建议可以反馈给我们。
标 题:
 *
内 容:
Email:  *
验证码:   刷新

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

 

 

Valid XHTML 1.0!
Copyright © 2007-2017  中国科学院国家天文台 - Feedback
Powered by CSpace