paper
2019
Extremes & hazards
Position or perspective paper
RNN / LSTM / ConvLSTM6 h–3 days Journal
2019-03-22
004
Mar 2019
anonymous
Electronics Letters
Interview on an RNN-based tropical cyclone intensity prediction model, arguing deep learning can address the black-box nature of typhoon forecasting.
interview
In one sentence. Interview on an RNN-based tropical cyclone intensity prediction model, arguing deep learning can address the black-box nature of typhoon forecasting.
Labels
- Topic
- Extremes & hazards
- Type
- Position or perspective paper
- Method
- RNN / LSTM / ConvLSTM
- Time scale
- 6 h–3 days
- Domain
- Regional
- Data
- Other
- Status
- Research
- Identifiers
- DOI:10.1049/el.2019.0887 OpenAlex:W4254899223
- Added
- 2026-10-22
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