Support vector machines for photometric redshift measurement of quasars

被引：2
|
作者：
Zheng, Hongwen [1 ,2 ]
Zhang, Yanxia
机构：
[1] Chinese Acad Sci, Natl Astron Observ, Key Lab Opt Astron, Datun Rd 20A, Beijing 100012, Peoples R China
[2] North China Elect Power Univ, Math & Phys Dept, Beijing, Peoples R China
来源：
SOFTWARE AND CYBERINFRASTRUCTURE FOR ASTRONOMY II | 2012年 / 8451卷
基金：
中国国家自然科学基金;
关键词：
techniques: photometric; galaxies: distances and redshifts; quasars: photometry; cosmology: observations; methods: data analysis; DIGITAL SKY SURVEY; CLASSIFICATION; GALAXIES; SDSS;
D O I：
10.1117/12.925761
中图分类号：
P1 [天文学];
学科分类号：
0704 ;
摘要：
Based on photometric and spectroscopic data of quasars from SDSS DR7 and UKDISS DR7, support vector machines (SVM) is applied to predict photometric redshifts of quasars. Different input patterns are tried and the best pattern is presented. Comparing the results using optical data with that using optical and infrared data, the experimental results show that the accuracy improves with data from more bands. In addition, the quasar sample is firstly clustered into two groups by one-class SVM, then the photometric redshifts of the two groups are separately estimated by means of SVM. The results based on the whole sample and the combined results from the two groups are comparable.
引用
收藏
页数：8
相关论文
共 50 条
  • [1] Estimating photometric redshifts of quasars using support vector machines
    Wang, Dan
    Zhang, Yanxia
    Zhao, Yongheng
    [J]. ASTRONOMICAL DATA ANALYSIS SOFTWARE AND SYSTEMS XVII, 2008, 394 : 509 - 512
  • [2] Support vector machines for photometric redshift estimation from broadband photometry
    Wang, Dan
    Zhang, Yanxia
    Zhao, Yongheng
    [J]. Data Science Journal, 2007, 6 (SUPPL.)
  • [3] Separating Quasars from Stars by Support Vector Machines
    Zhang, Yanxia
    Zheng, Hongwen
    Zhao, Yongheng
    [J]. SOFTWARE AND CYBERINFRASTRUCTURE FOR ASTRONOMY, 2010, 7740
  • [4] Discrimination Between Quasars and Stars by Support Vector Machines
    Zhang, Yanxia
    Zheng, Hongwen
    [J]. CO-EVOLUTION OF CENTRAL BLACK HOLES AND GALAXIES, 2010, (267): : 146 - 146
  • [5] Comparison of Approaches to Photometric Redshift Estimation of Quasars
    Tu, Yang
    Zhang, Yan-Xia
    Zhao, Yong-Heng
    Tian, Hai-Jun
    [J]. GALAXIES AT HIGH REDSHIFT AND THEIR EVOLUTION OVER COSMIC TIME, 2016, 11 (S319): : 146 - 146
  • [6] Estimating photometric redshifts using support vector machines
    Wadadekar, Y
    [J]. PUBLICATIONS OF THE ASTRONOMICAL SOCIETY OF THE PACIFIC, 2005, 117 (827) : 79 - 85
  • [7] ELM-KNN for photometric redshift estimation of quasars
    Zhang, Yanxia
    Tu, Yang
    Zhao, Yongheng
    Tian, Haijun
    [J]. ASTROINFORMATICS, 2017, 12 (S325): : 225 - 228
  • [8] ImPZ:: a new photometric redshift code for galaxies and quasars
    Babbedge, TSR
    Rowan-Robinson, M
    Gonzalez-Solares, E
    Polletta, M
    Berta, S
    Pérez-Fournon, I
    Oliver, S
    Salaman, DM
    Irwin, M
    Weatherley, SJ
    [J]. MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY, 2004, 353 (02) : 654 - 672
  • [9] Photometric redshift estimation for quasars by integration of KNN and SVM
    Bo Han
    Hong-Peng Ding
    Yan-Xia Zhang
    Yong-Heng Zhao
    [J]. Research in Astronomy and Astrophysics, 2016, 16 (05) : 33 - 42
  • [10] Influence of Different Samples on Photometric Redshift Estimation for Quasars
    Zhang, Yanxia
    Tu, Yang
    Zhao, Yongheng
    Tian, Haijun
    [J]. ASTRONOMICAL DATA ANALYSIS SOFTWARE AND SYSTEMS XXVI, 2019, 521 : 417 - 420
12345