NSSC OpenIR  > 空间环境部
应用数据挖掘技术的短期太阳耀斑预报模型
Alternative TitleShort-term solar flare forecasting model using datamining technique
李蓉; 崔延美; lirong@bao.ac.cn
Department空间环境部
Source Publication中国科学. 物理学, 力学, 天文学
2011
Volume41Issue:11Pages:1342-1350
ISSN1674-7275
Language中文
Keyword太阳耀斑 黑子数据 预报因子 决策树 分类规则
Abstract为了进一步探讨太阳耀斑与太阳黑子参量的关系,本文采集了大规模的活动区黑子数据,统计其与耀斑发生的产率关系,应用得到的拟和公式对原始数据计算得到规范化后的数据集。在此基础上使用数据挖掘技术对黑子耀斑数据建立决策树模型和建立分类规则,具体描述了黑子数据和太阳耀斑之间的相关性。最后应用这两种技术对活动区未来48h是否爆发耀斑给出了预报,预报结果具有较高的准确率和较低的虚报率。
Other AbstractIn order to study the correlation between the solar and sunspot parameters,a large scale of sunspots is collected,and the productivities with flare are calculated in this paper.After putting the original data into the fitting formula,the normalized data is obtained.Based on these data,decision tress and classification rule are constructed using datamining techniques,which describe concretely the correlation of sunspot and flare.Finally,these two modules give a forecasting about whether burst solar flare in region in future 48 hours.The results show a higher accuracy rate and a lower false alarm rate.
Indexed ByCSCD
Funding Project中国科学院空间科学与应用研究中心
Citation statistics
Document Type期刊论文
Identifierhttp://ir.nssc.ac.cn/handle/122/2894
Collection空间环境部
Corresponding Authorlirong@bao.ac.cn
Recommended Citation
GB/T 7714
李蓉,崔延美,lirong@bao.ac.cn. 应用数据挖掘技术的短期太阳耀斑预报模型[J]. 中国科学. 物理学, 力学, 天文学,2011,41(11):1342-1350.
APA 李蓉,崔延美,&lirong@bao.ac.cn.(2011).应用数据挖掘技术的短期太阳耀斑预报模型.中国科学. 物理学, 力学, 天文学,41(11),1342-1350.
MLA 李蓉,et al."应用数据挖掘技术的短期太阳耀斑预报模型".中国科学. 物理学, 力学, 天文学 41.11(2011):1342-1350.
Files in This Item: Download All
File Name/Size DocType Version Access License
201141111342.pdf(1094KB) 开放获取CC BY-NC-SAView Download
Related Services
Recommend this item
Bookmark
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[李蓉]'s Articles
[崔延美]'s Articles
[lirong@bao.ac.cn]'s Articles
Baidu academic
Similar articles in Baidu academic
[李蓉]'s Articles
[崔延美]'s Articles
[lirong@bao.ac.cn]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[李蓉]'s Articles
[崔延美]'s Articles
[lirong@bao.ac.cn]'s Articles
Terms of Use
No data!
Social Bookmark/Share
File name: 201141111342.pdf
Format: Adobe PDF
All comments (0)
No comment.
 

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