paper
2023
Local & station forecasting
Post-processing & calibration Application study
Classical ML (trees, GP, linear, kernels)Seasonal to annual Journal
2023-06-01
008
Jun 2023
Elton Rafael Alves, Márcio Nirlando Gomes Lopes, Fabricio Sales et al.
IEEE Latin America Transactions
GMDH model using lagged sea surface temperature predicts monthly rainfall in Pará, Brazil, with R 0.96 versus 0.82 for a multilayer perceptron.
A GMDH Approach for Forecast Monthly Rainfall in Southeast of Para
In one sentence. GMDH model using lagged sea surface temperature predicts monthly rainfall in Pará, Brazil, with R 0.96 versus 0.82 for a multilayer perceptron.
Labels
- Topic
- Local & station forecasting, Post-processing & calibration
- Type
- Application study
- Method
- Classical ML (trees, GP, linear, kernels)
- Time scale
- Seasonal to annual
- Domain
- Local / station
- Data
- Station / in-situ, Other
- Status
- Research
- Identifiers
- DOI:10.1109/tla.2023.10172135 OpenAlex:W4382935733
- Added
- 2026-10-22
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