Deep air learning: Interpolation, prediction, and feature analysis of fine-grained air quality

• Main Authors: QI, Zhongang, WANG, Tianchun, SONG, Guojie, HU, Weisong, LI, Xi, ZHANG, Zhongfei Mark
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2018
• Subjects: Air pollution; Analytical models; Atmospheric modeling; Deep Learning; Feature Analysis; Feature extraction; Feature Selection; Interpolation; Predictive models; Spatio-temporal Semi-supervised Learning; Databases and Information Systems; Environmental Sciences; Numerical Analysis and Scientific Computing
• Online Access: https://ink.library.smu.edu.sg/sis_research/3979; https://ink.library.smu.edu.sg/context/sis_research/article/4981/viewcontent/171100939.pdf
• Institution: Singapore Management University

The interpolation, prediction, and feature analysis of fine-gained air quality are three important topics in the area of urban air computing. The solutions to these topics can provide extremely useful information to support air pollution control, and consequently generate great societal and technica...