Name
Title | ||
|---|---|---|
Deep Air Learning: Interpolation, Prediction, and Feature Analysis of Fine-grained Air Quality. |
Abstract | ||
|---|---|---|
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 technical impacts. Most of the existing work solves the three problems separately by different models. In th... |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/TKDE.2018.2823740 | IEEE Transactions on Knowledge and Data Engineering |
Keywords | DocType | Volume |
Atmospheric modeling,Feature extraction,Semisupervised learning,Predictive models,Deep learning,Analytical models | Journal | 30 |
Issue | ISSN | Citations |
12 | 1041-4347 | 13 |
PageRank | References | Authors |
0.65 | 15 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Zhongang Qi | 1 | 90 | 6.90 |
| Tianchun Wang | 2 | 13 | 0.65 |
| Guojie Song | 3 | 762 | 57.31 |
| Weisong Hu | 4 | 62 | 5.76 |
| Xi Li | 5 | 1850 | 137.71 |
| Zhongfei (Mark) Zhang | 6 | 2451 | 164.30 |