paper
2022
Local & station forecasting
Applications & impacts New model or method
RNN / LSTM / ConvLSTM6 h–3 days Journal
2022-12-23
008
Dec 2022
Chuen-Jyh Chen, Chieh-Ni Huang, S. M. Yang
Journal of Intelligent & Fuzzy Systems
An LSTM with regression-based feature selection forecasts daily temperature from station variables for aviation safety, cutting RMSE from 4.03 to 2.22.
Application of deep learning to multivariate aviation weather forecasting by long short-term memory
In one sentence. An LSTM with regression-based feature selection forecasts daily temperature from station variables for aviation safety, cutting RMSE from 4.03 to 2.22.
Labels
- Topic
- Local & station forecasting, Applications & impacts
- Type
- New model or method
- Method
- RNN / LSTM / ConvLSTM
- Time scale
- 6 h–3 days
- Domain
- Local / station
- Data
- Station / in-situ
- Status
- Research
- Identifiers
- DOI:10.3233/jifs-223183 OpenAlex:W4312181817
- Added
- 2026-10-22
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