Particulate Matter Forecasting Using Different Deep Neural Network Topologies and Wavelets for Feature Augmentation

Particulate Matter Forecasting Using Different Deep Neural Network Topologies and Wavelets for Feature Augmentation

The concern about air pollution in urban areas has substantially increased worldwide. One of its main components, particulate matter (PM) with aerodynamic diameter of ≤2.5 µm (PM<sub>2.5</sub>), can be inhaled and deposited in deeper regions of the respiratory system, causing adverse eff...

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Bibliographic Details
Main Authors: Stephanie Lima Jorge Galvão, Júnia Cristina Ortiz Matos, Yasmin Kaore Lago Kitagawa, Flávio Santos Conterato, Davidson Martins Moreira, Prashant Kumar, Erick Giovani Sperandio Nascimento
Format: Article
Language:English
Published: MDPI AG 2022-09-01
Series:Atmosphere
Subjects:
particulate matter
air pollution
artificial neural networks
deep learning
forecasting
wavelets
Online Access:https://www.mdpi.com/2073-4433/13/9/1451

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