Estimation of microphysical parameters of atmospheric pollution using machine learning
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Author
Llerena, C.
Müller, D.
Adams, R.
Davey, N.
Sun, Y.
Attention
2299/22534
Abstract
The estimation of microphysical parameters of pollution (effective radius and complex refractive index) from optical aerosol parameters entails a complex problem. In previous work based on machine learning techniques, Artificial Neural Networks have been used to solve this problem. In this paper, the use of a classification and regression solution based on the k-Nearest Neighbor algorithm is proposed. Results show that this contribution achieves better results in terms of accuracy than the previous work.