paper
2022
Sub-seasonal to seasonal
Extremes & hazards New model or method
RNN / LSTM / ConvLSTMSeasonal to annual Journal
2022-11-09
012
Nov 2022
Zhiyong Wu, Hao Yin, Hai He et al.
Journal of Hydrology
Hybrid dynamic model and LSTM aim to improve seasonal drought prediction over China; the abstract is missing, so scope is inferred from the title.
Dynamic-LSTM hybrid models to improve seasonal drought predictions over China
In one sentence. Hybrid dynamic model and LSTM aim to improve seasonal drought prediction over China; the abstract is missing, so scope is inferred from the title.
Labels
- Topic
- Sub-seasonal to seasonal, Extremes & hazards
- Type
- New model or method
- Method
- RNN / LSTM / ConvLSTM
- Time scale
- Seasonal to annual
- Domain
- Regional
- Data
- Other
- Status
- Research
- Identifiers
- DOI:10.1016/j.jhydrol.2022.128706 OpenAlex:W4308601244
- Added
- 2026-10-22
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