Enhancing the Data Learning With Physical Knowledge in Fine-Grained Air Pollution Inference

Enhancing the Data Learning With Physical Knowledge in Fine-Grained Air Pollution Inference

Fine-grained air pollution monitoring has attracted increasing attention worldwide. Even with an increasing amount of both static and mobile sensing systems, an inference algorithm is still essential to achieve a comprehensive understanding of the urban atmospheric environment. Conventional physical...

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Bibliographic Details
Main Authors: Rui Ma, Ning Liu, Xiangxiang Xu, Yue Wang, Hae Young Noh, Pei Zhang, Lin Zhang
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Air pollution inference
data-driven method
multitask learning
physical model
Online Access:https://ieeexplore.ieee.org/document/9090816/

Internet

https://ieeexplore.ieee.org/document/9090816/

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