paper
2019
Extremes & hazards
Observations & remote sensing New model or method
RNN / LSTM / ConvLSTMCNN / U-Net Journal
2019-08-11
012
Aug 2019
Minhyung Lee, Soobong Lee, Jung-Hwan Lee et al.
Journal of Korean Institute of Industrial Engineers
Uses a CNN-LSTM on COMS satellite channels to estimate typhoon maximum wind speed, reaching 9.84 knot RMSE with the WV channel.
Predicting Maximum Wind Speed of Typhoons based on Convolutional Recurrent Neural Network via COMS Satellite Data
In one sentence. Uses a CNN-LSTM on COMS satellite channels to estimate typhoon maximum wind speed, reaching 9.84 knot RMSE with the WV channel.
Labels
- Topic
- Extremes & hazards, Observations & remote sensing
- Type
- New model or method
- Method
- RNN / LSTM / ConvLSTM, CNN / U-Net
- Domain
- Regional
- Data
- Satellite
- Status
- Research
- Identifiers
- DOI:10.7232/jkiie.2019.45.4.349 OpenAlex:W2968147280
- Added
- 2026-10-22
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