paper
2021
Extremes & hazards
New model or method
RNN / LSTM / ConvLSTM6 h–3 days Journal
2021-01-02
012
Jan 2021
Yusuke Igarashi, Yoshimitsu TAJIMA
Coastal Engineering Journal
RNN outperforms DNN for fast prediction of typhoon-driven storm surge time series at ten Tokyo Bay points, trained on 151 simulated typhoons.
Application of recurrent neural network for prediction of the time-varying storm surge
In one sentence. RNN outperforms DNN for fast prediction of typhoon-driven storm surge time series at ten Tokyo Bay points, trained on 151 simulated typhoons.
Labels
- Topic
- Extremes & hazards
- Type
- New model or method
- Method
- RNN / LSTM / ConvLSTM
- Time scale
- 6 h–3 days
- Domain
- Local / station
- Data
- Other
- Status
- Research
- Identifiers
- DOI:10.1080/21664250.2020.1868736 OpenAlex:W3124382064
- Added
- 2026-10-22
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