APPLIED LASER, Volume. 45, Issue 1, 75(2025)

Prediction Method of Laser Cleaning Composite Coating Thickness Based on PSO-SVR

Hou Xingqiang, Cheng Wei*, Ren Yuan, Su Zhenwei, Zhang Yanlu, Gao Qiuling, and Dai Na
Author Affiliations
  • Institute of Laser, Qilu University of Technology (Shandong Academy of Sciences), Jinan 250353, Shandong, China
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    References(4)

    [7] [7] YU J H, CHEN Y F. Prediction of simulation parameters of fiber laser cleaning range hood based on BP neural network[J]. Journal of Physics: Conference Series, 2021, 1820(1): 012118.

    [8] [8] ZHANG Y H, ZHAO Y J, SUN B, et al. Visualizing the prediction of laser cleaning: A dynamic preview method with a multi-scale conditional generative adversarial network[J]. Applied Optics, 2019, 58(31): 8344-8353.

    [12] [12] CORTES C, VAPNIK V. Support-vector networks[J]. Machine Learning, 1995, 20(3): 273-297.

    [14] [14] XIE R B, YANG S Z, SUN C Z, et al. Prediction model of needle valve body extrusion grinding process based on PSO-SVR[J]. Journal of Physics: Conference Series, 2021, 2024(1): 012041.

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    Hou Xingqiang, Cheng Wei, Ren Yuan, Su Zhenwei, Zhang Yanlu, Gao Qiuling, Dai Na. Prediction Method of Laser Cleaning Composite Coating Thickness Based on PSO-SVR[J]. APPLIED LASER, 2025, 45(1): 75

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    Paper Information

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    Received: May. 15, 2023

    Accepted: Apr. 17, 2025

    Published Online: Apr. 17, 2025

    The Author Email: Cheng Wei (chengweijob@163.com)

    DOI:10.14128/j.cnki.al.20254501.075

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