| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 6905744 | Applied Soft Computing | 2014 | 7 Pages |
Abstract
- Address the potential of learning machine to forecast ground-level ozone in urban area.
- Summarize the existing learning machines used to predict ground-level ozone.
- Compare the performance of commented models via practical case in Hong Kong.
- Address the underlying philosophy of using learning machine in ozone related prediction.
Keywords
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Science Applications
Authors
Wei-Zhen Lu, Dong Wang,