paper
2019
Local & station forecasting
Post-processing & calibration New model or method
Classical ML (trees, GP, linear, kernels)6 h–3 days Journal
2019-07-28
008
Jul 2019
Tianwen Huang, Fei Jiao
The Computer Journal
Instance-based transfer learning borrows records from neighboring cities to extend scarce station data for temperature and precipitation forecasts in Zhaoqing, China.
Study on Data Transfer in Meteorological Forecast of Small and Medium-Sized Cities and Its Application in Zhaoqing City
In one sentence. Instance-based transfer learning borrows records from neighboring cities to extend scarce station data for temperature and precipitation forecasts in Zhaoqing, China.
Labels
- Topic
- Local & station forecasting, Post-processing & calibration
- Type
- New model or method
- Method
- Classical ML (trees, GP, linear, kernels)
- Time scale
- 6 h–3 days
- Domain
- Local / station
- Data
- Station / in-situ
- Status
- Research
- Identifiers
- DOI:10.1093/comjnl/bxz087 OpenAlex:W2973161963
- Added
- 2026-10-22
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