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Erschienen in:
2014 | OriginalPaper | Buchkapitel
Fine-Grained Air Quality Monitoring Based on Gaussian Process Regression
verfasst von : Yun Cheng, Xiucheng Li, Zhijun Li, Shouxu Jiang, Xiaofan Jiang
Erschienen in: Neural Information Processing
Verlag: Springer International Publishing
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Air quality is attracting more and more attentions in recent years due to the deteriorating environment, and
PM
2.5
is the main contaminant in a lot of areas. Existing softwares that report the level of
PM
2.5
can provide only the value in the city level, which may indeed varies greatly among different areas in the city. To help people know about the exact air quality around them, we deployed 51 carefully designed devices to measure the
PM
2.5
at these places and present a Gaussian Process based inference model to estimate the value at any place. The proposed method is evaluated on the real data and compared to some related methods. The experimental results prove the effectiveness of our method.