APPLIED LASER, Volume. 44, Issue 11, 102(2024)

The Detection Method of Mixed Gas Concentration Using Improved Extreme Learning Machine

Wang Yinsong, Li Zhen*, Kong Qingmei, and Gao Jianqiang
Author Affiliations
  • Department of Automation, North China Electric Power University, Baoding 071003, Hebei, China
  • show less
    References(5)

    [2] [2] CHAO X, JEFFRIES J B, HANSON R K. Real-time, in situ, continuous monitoring of CO in a pulverized-coal-fired power plant with a 2.3 μm laser absorption sensor[J]. Applied Physics B, 2013, 110(3): 359-365.

    [3] [3] ZHANG E J, TENG C C, VAN KESSEL T G, et al. Field deployment of a portable optical spectrometer for methane fugitive emissions monitoring on oil and gas well pads[J]. Sensors, 2019, 19(12): 2707.

    [6] [6] DU J Y, YIN C, DENG J, et al. Study on influence of temperature and pressure in TDLAS trace CO detection[C]//2017 IEEE 2nd Information Technology, Networking, Electronic and Automation Control Conference (ITNEC). Chengdu: IEEE, 2017: 248-252.

    [9] [9] LI G L, ZHANG X N, ZHANG Z C, et al. Performance enhancement of a near-infrared NH3 sensor based on PSO-LSSVM for denitrification industrial process[J]. Infrared Physics & Technology, 2022, 125: 104226.

    [11] [11] HUANG G B, ZHU Q Y, SIEW C K. Extreme learning machine: A new learning scheme of feedforward neural networks[C]//2004 IEEE International Joint Conference on Neural Networks (IEEE Cat. No.04CH37541). Budapest, Hungary: 2004, IEEE, 985-990.

    Tools

    Get Citation

    Copy Citation Text

    Wang Yinsong, Li Zhen, Kong Qingmei, Gao Jianqiang. The Detection Method of Mixed Gas Concentration Using Improved Extreme Learning Machine[J]. APPLIED LASER, 2024, 44(11): 102

    Download Citation

    EndNote(RIS)BibTexPlain Text
    Save article for my favorites
    Paper Information

    Received: Apr. 1, 2023

    Accepted: Mar. 11, 2025

    Published Online: Mar. 11, 2025

    The Author Email: Zhen Li (826262798@qq.com)

    DOI:10.14128/j.cnki.al.20244411.102

    Topics