An Automatic Method for Selecting Special and Rare Celestial Objects in Massive Spectra

摘要：

　　We proposed an automatic method for searching special and rare celestial objects in the massive spectra of the Sloan digital sky survey(SDSS).The data mining technique is employed and the massive SDSS spectra are identified quickly and efficiently.The high-dimensional spectra are mapped to feature space constructed by the principal component analysis(PCA),and dimensionality reduction is carried out accordingly.Massive SDSS spectra are classified by a well-trained support vector machine(SVM)and most of the noncandidates are excluded.Parameter optimization is also studied to guarantee the accuracy of PCA and SVM.Experiments show that this novel method can find rare celestial objects in an effective and efficient manner.We report the identification of six new white dwarfmain sequence(WDMS).

关键词： Data mining Massive spectra PCA SVM

作者: Wenyu Wang Bin Jiang

作者单位: School of Mechanical,Electrical and Information Engineering,Shandong University,Weihai 264209,China

会议类型: 国际会议

会议名称: The 2015 Chinese Intelligent Automation Conference(2015中国智能自动化会议)

会议地点: 福州

会议语种:英文

页码: 209-218

在线出版日期: 2015-05-08（万方平台首次上网日期，不代表论文的发表时间）