paper
2021
Local & station forecasting
New model or method
RNN / LSTM / ConvLSTMClassical ML (trees, GP, linear, kernels)6 h–3 days Journal
2021-01-19
018
Jan 2021
Toni Toharudin, Resa Septiani Pontoh, Rezzy Eko Caraka et al.
Communications in Statistics - Simulation and Computation
Compares LSTM and Facebook Prophet on five years of daily air temperature in Bandung; each performs better on different variables, with small RMSE differences.
Employing long short-term memory and Facebook prophet model in air temperature forecasting
In one sentence. Compares LSTM and Facebook Prophet on five years of daily air temperature in Bandung; each performs better on different variables, with small RMSE differences.
Labels
- Topic
- Local & station forecasting
- Type
- New model or method
- Method
- RNN / LSTM / ConvLSTM, Classical ML (trees, GP, linear, kernels)
- Time scale
- 6 h–3 days
- Domain
- Local / station
- Data
- Station / in-situ
- Status
- Research
- Identifiers
- DOI:10.1080/03610918.2020.1854302 OpenAlex:W3124899688
- Added
- 2026-10-22
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