A new hybrid deep neural network for multiple sites PM2.5 forecasting-Reference-Cited by-同舟云学术

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A new hybrid deep neural network for multiple sites PM2.5 forecasting

Published:2024-10 Issue: Volume:473 Page:143542
ISSN:0959-6526
Container-title:Journal of Cleaner Production
language:en
Short-container-title:Journal of Cleaner Production

Author:

Teng Mengfan,Li Siwei^ORCID,Yang Jie,Chen Jiarui,Fan Chunying,Ding Yu

Publisher

Elsevier BV

Reference59 articles.

1. Assessing the accuracy of ANFIS, EEMD-GRNN, PCR, and MLR models in predicting PM2.5;Ausati;Atmos. Environ.,2016

2. A survey on air pollutant PM2.5 prediction using random forest model;Babu;Environmental Health Engineering And Management Journal,2023

3. PM10 and PM2.5 real-time prediction models using an interpolated convolutional neural network;Chae;Sci. Rep.,2021

4. Acute respiratory response to individual particle exposure (PM1. 0, PM2. 5 and PM10) in the elderly with and without chronic respiratory diseases;Chen;Environ. Pollut.,2021

5. Influence of meteorological conditions on PM2.5 concentrations across China: a review of methodology and mechanism;Chen;Environ. Int.,2020

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