Deep Learning From Spatio-Temporal Data Using Orthogonal Regularizaion Residual CNN for Air Prediction

Deep Learning From Spatio-Temporal Data Using Orthogonal Regularizaion Residual CNN for Air Prediction

Air pollution is harmful to human health and restricts economic development, so predicting when and where air pollution will occur is a challenging and important issue, especially in fields of urban planning, factory production and human activities. In this paper, we propose a deep Spatio-Temporal O...

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Bibliographic Details
Main Authors: Lei Zhang, Dong Li, Quansheng Guo
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Deep learning
urban computing
spatio-temporal big data
orthogonal regularization
residual network
Online Access:https://ieeexplore.ieee.org/document/9056826/

Internet

https://ieeexplore.ieee.org/document/9056826/

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