• Spectroscopy and Spectral Analysis
  • Vol. 39, Issue 9, 2693 (2019)
MU Yong-huan1、*, QIU Bo1, WEI Shi-ya1, SONG Tao1, ZHENG Zi-peng1, and GUO Ping2
Author Affiliations
  • 1[in Chinese]
  • 2[in Chinese]
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    DOI: 10.3964/j.issn.1000-0593(2019)09-2693-05 Cite this Article
    MU Yong-huan, QIU Bo, WEI Shi-ya, SONG Tao, ZHENG Zi-peng, GUO Ping. Regression Prediction of Photometric Redshift Based on Particle Warm Optimization Neural Network Algorithm[J]. Spectroscopy and Spectral Analysis, 2019, 39(9): 2693 Copy Citation Text show less
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    [2] Kügler S D, Gianniotis N, Kai L P. A Spectral Model for Multimodal Redshift Estimation (C). Computational Intelligence, IEEE Xplore, 2016. 1.

    [3] Zheng H, Zhang Y. Review of Techniques for Photometric Redshift Estimation. International Society for Optics and Photonics, Software and Cyberinfrastructure for Astronomy Ⅱ, 2012. 8451.

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    [9] Beck R, Dobos L, Budavári T, et al. Monthly Notices of the Royal Astronomical Society, 2016, 460(2): 1371.

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    CLP Journals

    [1] WU Kuang, SUN Chun, CAO Guan-long, QIU Bo, YAO Lin, ZHANG Ming-ru, ZHANG Li-wen. An Algorithm for Redshift Estimation of Photometric Images Using Convolutional Neural Networks[J]. Spectroscopy and Spectral Analysis, 2023, 43(8): 2529

    MU Yong-huan, QIU Bo, WEI Shi-ya, SONG Tao, ZHENG Zi-peng, GUO Ping. Regression Prediction of Photometric Redshift Based on Particle Warm Optimization Neural Network Algorithm[J]. Spectroscopy and Spectral Analysis, 2019, 39(9): 2693
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