Research on calibration model of light scattering sensor based on random forest

Pengxu Yi; Hong Lin; RuoMeng Ma

doi:10.1117/12.3025136

28 March 2024 Research on calibration model of light scattering sensor based on random forest

Pengxu Yi, Hong Lin, RuoMeng Ma

Proceedings Volume 13091, Fifteenth International Conference on Signal Processing Systems (ICSPS 2023); 130912F (2024) https://doi.org/10.1117/12.3025136
Event: Fifteenth International Conference on Signal Processing Systems (ICSPS 2023), 2023, Xi’an, China

Abstract

Particle pollution has seriously affected the environment and human health. The monitoring of ambient air particles has become more normalized, and more and more cities are using micro online environmental air quality monitors as a supplement to existing national control stations. Now, high-precision β The Random forest model was established based on β-ray instrument, and the calibration of light scattering sensor was carried out. The correlation coefficient R2 increased from 0.77 before calibration to 0.97, and the relative expanded uncertainty of Random forest prediction results was 0.46%. The results indicate that studying the algorithm model can effectively reduce the measurement error of light scattering sensors, improve the accuracy and availability of micro station data.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Pengxu Yi, Hong Lin, and RuoMeng Ma "Research on calibration model of light scattering sensor based on random forest", Proc. SPIE 13091, Fifteenth International Conference on Signal Processing Systems (ICSPS 2023), 130912F (28 March 2024); https://doi.org/10.1117/12.3025136

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