Applying PCA to Deep Learning Forecasting Models for Predicting PM<sub>2.5</sub>

Applying PCA to Deep Learning Forecasting Models for Predicting PM<sub>2.5</sub>

Fine particulate matter (PM<sub>2.5</sub>) is one of the main air pollution problems that occur in major cities around the world. A country’s PM<sub>2.5</sub> can be affected not only by country factors but also by the neighboring country’s air quality factors. Therefore, for...

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Bibliographic Details
Main Authors: Sang Won Choi, Brian H. S. Kim
Format: Article
Language:English
Published: MDPI AG 2021-03-01
Series:Sustainability
Subjects:
principal components analysis (PCA)
PM<sub>2.5</sub>
recurrent neural network RNN)
long short-term memory (LSTM)
bidirectional LSTM (BiLSTM)
deep learning
Online Access:https://www.mdpi.com/2071-1050/13/7/3726

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https://www.mdpi.com/2071-1050/13/7/3726

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