Acta Optica Sinica, Volume. 44, Issue 24, 2401004(2024)

Application of Bidirectional Long Short‐Term Memory Network in Doppler Lidar Wind Profile Prediction

Wenchao Lian1, Xiaoquan Song1,2、*, Zhaoyang Hao1, and Ping Jiang1
Author Affiliations
  • 1College of Marine Technology, Faculty of Information Science and Engineering, Ocean University of China, Qingdao 266100, Shandong , China
  • 2Laboratory for Regional Oceanography and Numerical Modeling, Qingdao Marine Science and Technology Center, Qingdao 266237, Shandong , China
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    References(24)

    [1] Fu Y Y, Song X Q, Lian W C. Lidar observations of boundary layer low-level jet and its effect on PM2.5[J]. Acta Optica Sinica, 43, 1899909(2023).

    [4] Chen Z, Li J H, Guo J H et al. Research progress of wind energy resource assessment technology under climate change[J]. Sino-Global Energy, 24, 14-19(2019).

    [18] Bouvrie J. Notes on convolutional neural networks[J]. In Practice, 47-60(2006).

    [22] Xu H, Sun D F, Li J B. Coherence analysis of echoes from coherent wind lidar[J]. Laser & Optoelectronics Progress, 60, 1428003(2023).

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    Wenchao Lian, Xiaoquan Song, Zhaoyang Hao, Ping Jiang. Application of Bidirectional Long Short‐Term Memory Network in Doppler Lidar Wind Profile Prediction[J]. Acta Optica Sinica, 2024, 44(24): 2401004

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    Paper Information

    Category: Atmospheric Optics and Oceanic Optics

    Received: Apr. 22, 2024

    Accepted: May. 13, 2024

    Published Online: Dec. 16, 2024

    The Author Email: Xiaoquan Song (songxq@ouc.edu.cn)

    DOI:10.3788/AOS240891

    CSTR:32393.14.AOS240891

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