A Novel Short-Term PM <sub>2.5</sub> Forecasting Approach Using Secondary Decomposition and a Hybrid Deep Learning Model-Reference-Cited by-同舟云学术

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A Novel Short-Term PM <sub>2.5</sub> Forecasting Approach Using Secondary Decomposition and a Hybrid Deep Learning Model

Published:2024 Issue: Volume: Page:
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Author:

Liu Ruru,Xu Liping,Zeng Tao,Luo Tao,Wang Mengfei,Zhou Yuming,Chen Chunpeng,Zhao Shuo

Publisher

Elsevier BV

Reference41 articles.

1. Is the sky of smart city bluer? evidence from satellite monitoring data;K Gao;Journal of Environmental Management,2022

2. The heterogeneous effects of socioeconomic determinants on PM 2.5 concentrations using a two-step panel quantile regression;D Yan;Applied Energy,2020

3. A method of gas-related pollution source layout based on multi-source data: A case study of shaanxi province, china;Y Yang;Journal of Environmental Management,2023

4. Characteristics of PM 2.5 pollution in beijing after the improvement of air quality;X Huang;Journal of environmental sciences,2021

5. The role of fossil fuel combustion metals in PM 2.5 air pollution health associations;P Maciejczyk;Atmosphere,2021

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