paper
2022
Local & station forecasting
New model or method
CNN / U-NetRNN / LSTM / ConvLSTM6 h–3 days Journal
2022-06-14
008
Jun 2022
Sercan Yalçın
Concurrency and Computation Practice and Experience
Hybrid CNN-LSTM model forecasts temperature, humidity, pressure and wind speed time series, reporting lower errors than machine learning and deep learning baselines.
Weather parameters forecasting with time series using deep hybrid neural networks
In one sentence. Hybrid CNN-LSTM model forecasts temperature, humidity, pressure and wind speed time series, reporting lower errors than machine learning and deep learning baselines.
Labels
- Topic
- Local & station forecasting
- Type
- New model or method
- Method
- CNN / U-Net, RNN / LSTM / ConvLSTM
- Time scale
- 6 h–3 days
- Domain
- Local / station
- Data
- Station / in-situ
- Status
- Research
- Identifiers
- DOI:10.1002/cpe.7141 OpenAlex:W4282943735
- Added
- 2026-10-22
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