Adaptive Deep Learning-Based Air Quality Prediction Model Using the Most Relevant Spatial-Temporal Relations

Adaptive Deep Learning-Based Air Quality Prediction Model Using the Most Relevant Spatial-Temporal Relations

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Air pollution has become an extremely serious problem, with particulate matter having a significantly greater impact on human health than other contaminants. The small diameter of fine particulate matter (PM2.5) allows it to penetrate deep into the alveoli as far as the bronchioles, interfering with...

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Bibliographic Details
Main Authors: Ping-Wei Soh, Jia-Wei Chang, Jen-Wei Huang
Format: Article
Language:English
Published: IEEE 2018-01-01
Series:IEEE Access
Subjects:
Dynamic time warping(DTW)
convolutional neural network(CNN)
long-short-term memory(LSTM)
spatio-temporal analysis
big data
air quality forecast
Online Access:https://ieeexplore.ieee.org/document/8392677/

Internet

https://ieeexplore.ieee.org/document/8392677/

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