Hourly PM2.5 concentration forecast using stacked autoencoder model with emphasis on seasonality

Accurate PM2.5 forecasting provides a possibility for establishing an early warning system to notify the public and take precautionary measures to prevent negative effects on ambient air quality and public health. Considering strong seasonal variation in meteorological conditions, in this paper, a s...

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Bibliographic Details
Published in:	Journal of cleaner production Vol. 224; pp. 739 - 750
Main Authors:	Bai, Yun, Li, Yong, Zeng, Bo, Li, Chuan, Zhang, Jin
Format:	Journal Article
Language:	English
Published:	Elsevier Ltd 01.07.2019
Subjects:	air quality China data collection early warning systems environmental monitoring Forecasting Meteorological data meteorological parameters neural networks particulates PM2.5 public health seasonal variation Seasonality Stacked autoencoder time series analysis China Stacked autoencoder Meteorological data Forecasting PM2.5 Seasonality
ISSN:	0959-6526, 1879-1786
Online Access:	Get full text
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