Hybrid interpretable predictive machine learning model for air pollution prediction

Air pollution prediction is a burning issue, as pollutants can harm human health. Traditional machine learning models usually aim to improve the overall prediction accuracy but neglect the accuracy for peak values. Moreover, these models are not interpretable. They fail to explain the interactions b...

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Bibliographic Details

Main Authors:	Yuanlin Gu, Baihua Li, Qinggang Meng
Format:	Default Article
Published:	2021
Subjects:	Air pollution prediction Interpretable machine learning Neural network NARMAX model
Online Access:	https://hdl.handle.net/2134/16887352.v1
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