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

• 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

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...