Articles | Volume 13, issue 4
Atmos. Meas. Tech., 13, 1693–1707, 2020
https://doi.org/10.5194/amt-13-1693-2020
Atmos. Meas. Tech., 13, 1693–1707, 2020
https://doi.org/10.5194/amt-13-1693-2020

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 et al.

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Evaluation and Calibration of a Low-cost Particle Sensor in Ambient Conditions Using Machine Learning Methods M. Si https://doi.org/10.5281/zenodo.3473833

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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).