PM2.5 Prediction Using Genetic Algorithm-Based Feature Selection and Encoder-Decoder Model

PM2.5 Prediction Using Genetic Algorithm-Based Feature Selection and Encoder-Decoder Model

The concentration of fine particulate matter (PM2.5), which represents inhalable particles with diameters of 2.5 micrometers and smaller, is a vital air quality index. Such particles can penetrate deep into the human lungs and severely affect human health. This paper studies accurate PM2.5 predictio...

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Bibliographic Details
Main Authors: Minh Hieu Nguyen, Phi Le Nguyen, Kien Nguyen, Van An Le, Thanh-Hung Nguyen, Yusheng Ji
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
PM 25
genetic algorithm
feature selection
long short-term memory
encoder-decoder model
Online Access:https://ieeexplore.ieee.org/document/9399408/
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https://ieeexplore.ieee.org/document/9399408/

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