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一种晚型天体光谱离群数据挖掘系统 被引量:1

A Late-Type Star Spectra Outlier Data Mining System
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摘要 探索海量的M型恒星中具有磁活动、巨星等较特殊、稀有的天体,对于后续观测、银河系结构、演化等科学研究具有重要的意义,针对M型恒星光谱特征线出现在子空间中的局部偏离,设计并实现了晚型恒星离群数据挖掘系统。首先采用稀疏因子和稀疏度系数度量样本在属性空间上的分布特征,并在此基础上对M型恒星光谱特征线进行离散化、降维等预处理,获得光谱子空间;然后采用微粒群算法搜索离群子空间,并证认子空间内光谱是否离群;此外,选择SDSS M型光谱特征线指数集为样本,实验分析了稀疏因子和稀疏度系数的设置对离群结果的影响,并将离群挖掘结果与SDSS提供光谱型等参数对照,表明利用该系统实现晚型恒星光谱特征线局部离群数据挖掘是可行并有价值的。 In M star population ,some special objects ,which may be of magnetic activity ,may be giant stars ,or may be of other rare properties ,are very important for the follow-up observation and the scientific research on galactic structure and evolution . For local bias of M-type star spectral characteristic lines contained in subspace ,a late-type star spectra outlier data mining system is given in the present paper .Firstly ,for the sample of M stellar spectral characteristic lines indices ,its distribution characteris-tics in attribute spaces are measured by using the sparse factor and sparsity coefficient ,and then this sample is discretized and di-mension-reduced to the spectral subspace .Secondly ,local outlier subspaces are extracted by PSO (particle swarm optimization ) algorithm and identified .Additionally ,the effects of sparse coefficient and sparse factor on the number of outliers are discussed by experiments on the sample of SDSS M stellar spectral line index set ,and the outliers are compared with spectral type provided by SDSS .In this way ,the feasibility and value of this system were validated .
出处 《光谱学与光谱分析》 SCIE EI CAS CSCD 北大核心 2014年第5期1421-1424,共4页 Spectroscopy and Spectral Analysis
基金 国家自然科学基金项目(41372349 61272263) 山西省自然科学基金项目(2012011011-4)资助
关键词 局部离群 光谱特征线 子空间 Local outlier Spectra characteristic line Subspace
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参考文献14

  • 1Christopher P Ahn, Rachael Alexandroff, Carlos Allende Prieto, et al. Astrophysical Journal Supplement, 2014, 211(17): 16.
  • 2Cui Xiangqun, Zhao Yongheng, Chu Yaoquan, et al. Research in Astronomy and Astrophysics, 2012, 12(9): 1197.
  • 3Luo Ali, Zhang Haotong, Zhao Yongheng, et al. Research in Astronomy and Astrophysics, 2012, 12(9): 1243.
  • 4Brescia Massimo, Longo Giuseppe. Nuclear Instruments and Methods in Physics Research A, 2013, 720(8): 92.
  • 5Casini R, Ramos A A; Lites B W, et al. The Astrophysical Journal, 2013, 773(8):180.
  • 6Navarro S G, Corradi R L M, Mampaso A. Astronomy & Astrophysics, 2012, 538(A76): 14.
  • 7Meusinger H, Schalldach P, Scholz R D. et al. Astronomy & Astrophysics, 2012, 541(A77): 27.
  • 8Almeida J S, Prieto C A. The Astrophysical Journal, 2013, 763(1) : 50.
  • 9Adam Rogers, Jason D Fiege. The Astrophysical Journal, 2011, 727(2): 80.
  • 10Wei Peng, Luo Ali, Li Yinbi, et al. Monthly Notices of the Royal Astronomical Society, 2013, 431(3): 1800.

二级参考文献13

  • 1刘中田,李乡儒,吴福朝,赵永恒.基于小波特征的M型星自动识别方法[J].电子学报,2007,35(1):157-160. 被引量:11
  • 2张继福,蔡江辉.面向LAMOST的天体光谱离群数据挖掘系统研究[J].光谱学与光谱分析,2007,27(3):606-609. 被引量:6
  • 3蒋义勇,张继福,张素兰.基于链表结构的概念格渐进式构造[J].计算机工程与应用,2007,43(11):178-180. 被引量:11
  • 4Knorr E M, Ng R T. Algorithms formining distance-based outliers in large datasets. In: Proceedings of the 24th International Conference on Very Large Data Bases. San Francisco, USA: Morgan Kaufmann Publishers, 1998. 392-403.
  • 5Han J W, Kamber M. Data Mining Concepts and Techniques. San Francisco: Morgan Kaufmann Publishers, 2001.
  • 6Barnett V, Lewis T. Outliers in Statistical Data. New York: John Wiley-Sons, 1994.
  • 7Arning A, Agrawal R, Rghavan P. A linear method for deviation detection in large database. In: Proceedings of the 2nd International Conference on Knowledge Discovery and Data Mining. Portlan, Oregon: Morgan Kaufmann Publishers. 1996. 164-169.
  • 8Breunig M M, Kriegel H P, Ng R T, Sander J. LOF: identifying density-based local outliers. ACM Special Interest Group on Management of Data Record, 2000, 29(2): 93-104.
  • 9Agarwal C, Yu S. An effective and efficient algorithm for high-dimensional outlier detection. The International Journal on Very Large Data Bases, 2005, 14(2): 211-221.
  • 10Wille R. Restructuring lattice theory: an approach based on hierarchies of concepts. Ordered Sets, 1982, 11(5): 445-470.

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