Time-Series Data-Driven PM<sub>2.5</sub> Forecasting: From Theoretical Framework to Empirical Analysis

Time-Series Data-Driven PM<sub>2.5</sub> Forecasting: From Theoretical Framework to Empirical Analysis

PM<sub>2.5</sub> in air pollution poses a significant threat to public health and the ecological environment. There is an urgent need to develop accurate PM<sub>2.5</sub> prediction models to support decision-making and reduce risks. This review comprehensively explores the p...

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Bibliographic Details
Main Authors: Chunlai Wu, Ruiyang Wang, Siyu Lu, Jiawei Tian, Lirong Yin, Lei Wang, Wenfeng Zheng
Format: Article
Language:English
Published: MDPI AG 2025-02-01
Series:Atmosphere
Subjects:
PM<sub>2.5</sub>
deep learning
bibliometric analysis
LSTM
transformer
time-series
Online Access:https://www.mdpi.com/2073-4433/16/3/292
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