An Intelligent Time Series Model Based on Hybrid Methodology for Forecasting Concentrations of Significant Air Pollutants

An Intelligent Time Series Model Based on Hybrid Methodology for Forecasting Concentrations of Significant Air Pollutants

Rapid industrialization and urban development are the main causes of air pollution, leading to daily air quality and health problems. To find significant pollutants and forecast their concentrations, in this study, we used a hybrid methodology, including integrated variable selection, autoregressive...

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Bibliographic Details
Main Authors: Ching-Hsue Cheng, Ming-Chi Tsai
Format: Article
Language:English
Published: MDPI AG 2022-07-01
Series:Atmosphere
Subjects:
air pollution
variable selection
autoregressive distributed lag model
air quality rules
time-series forecast model
Online Access:https://www.mdpi.com/2073-4433/13/7/1055

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