Atmospheric Measurement Techniques
Atmospheric Measurement Techniques
AMT
Articles | Volume 13, issue 4
Articles | Volume 13, issue 4
https://doi.org/10.5194/amt-13-1693-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-13-1693-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 13, issue 4
Research article
 | 
07 Apr 2020
Research article |  | 07 Apr 2020

Evaluation and calibration of a low-cost particle sensor in ambient conditions using machine-learning methods

Minxing Si, Ying Xiong, Shan Du, and Ke Du

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Short summary
The study evaluated the performance of a low-cost PM sensor in ambient conditions and calibrated its readings using simple linear regression (SLR), multiple linear regression (MLR), and two more powerful machine-learning algorithms with random search techniques for the best model architectures. The two machine-learning algorithms are XGBoost and a feedforward neural network (NN).
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