A Wavelet PM2.5 Prediction System Using Optimized Kernel Extreme Learning with Boruta-XGBoost Feature Selection

A Wavelet PM2.5 Prediction System Using Optimized Kernel Extreme Learning with Boruta-XGBoost Feature Selection

The fine particulate matter (PM2.5) concentration has been a vital source of info and an essential indicator for measuring and studying the concentration of other air pollutants. It is crucial to realize more accurate predictions of PM2.5 and establish a high-accuracy PM2.5 prediction model due to t...

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Bibliographic Details
Main Authors:	Ali Asghar Heidari, Mehdi Akhoondzadeh, Huiling Chen
Format:	Article
Language:	English
Published:	MDPI AG 2022-09-01
Series:	Mathematics
Subjects:	air pollution optimization PM2.5 prediction kernel extreme learning machine machine learning
Online Access:	https://www.mdpi.com/2227-7390/10/19/3566

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