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2018 | OriginalPaper | Chapter

Estimation of Microphysical Parameters of Atmospheric Pollution Using Machine Learning

Authors : C. Llerena, D. Müller, R. Adams, N. Davey, Y. Sun

Published in: Artificial Neural Networks and Machine Learning – ICANN 2018

Publisher: Springer International Publishing

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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.

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Title: Estimation of Microphysical Parameters of Atmospheric Pollution Using Machine Learning
Authors: C. Llerena
D. Müller
R. Adams
N. Davey
Y. Sun
Publisher: Springer International Publishing
Book: Artificial Neural Networks and Machine Learning – ICANN 2018
Print ISBN: 978-3-030-01417-9

Electronic ISBN: 978-3-030-01418-6

Copyright Year: 2018
DOI: https://doi.org/10.1007/978-3-030-01418-6_57

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