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Data Mining of Cataclysmic Variables Candidates in Massive Spectra
Jiang, Bin1,2; Luo A-li1; Zhao Yong-heng1
2011-08-01
Source PublicationSPECTROSCOPY AND SPECTRAL ANALYSIS
Volume31Issue:8Pages:2278-2282
AbstractAn automatic and efficient method for LAMOST' s massive spectral data reduction is presented in this paper. The identified cataclysmic variables were selected as templates to construct the feature space by PCA (the principal component analysis), and most of the non-candidates were excluded by the method using support vector machine. Template matching strategy was used to identify the final candidates which were analyzed to complement the templates as feedback. Fifty eight new CVs candidates were found in the experiment, showing that our approach to finding special celestial bodies can be practical in LAMOST.
KeywordCataclysmic Variables Data Mining Pca Svm
DOI10.3964/j.issn.1000-0593(2011)08-2278-05
Indexed BySCI
Language英语
WOS IDWOS:000293681300059
Citation statistics
Cited Times:1[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.bao.ac.cn/handle/114a11/7897
Collection光学天文研究部
Affiliation1.Natl Astron Observ, Key Lab Opt Astron, Beijing 100012, Peoples R China
2.Shandong Univ, Sch Mech Elect & Informat Engn, Weihai 264209, Peoples R China
Recommended Citation
GB/T 7714
Jiang, Bin,Luo A-li,Zhao Yong-heng. Data Mining of Cataclysmic Variables Candidates in Massive Spectra[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS,2011,31(8):2278-2282.
APA Jiang, Bin,Luo A-li,&Zhao Yong-heng.(2011).Data Mining of Cataclysmic Variables Candidates in Massive Spectra.SPECTROSCOPY AND SPECTRAL ANALYSIS,31(8),2278-2282.
MLA Jiang, Bin,et al."Data Mining of Cataclysmic Variables Candidates in Massive Spectra".SPECTROSCOPY AND SPECTRAL ANALYSIS 31.8(2011):2278-2282.
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