paper
2022
Local & station forecasting
Application study
Classical ML (trees, GP, linear, kernels)6 h–3 days Journal
2022-01-01
004
Jan 2022
Israa Jasim .., Bashar Talib Al-Nuaimi, Ther Intisar Baker
Journal of artificial intelligence and metaheuristics.
Compares random forest, decision tree and gradient boosting for Iraq weather variables from NASA data; random forest reaches 92% accuracy.
Weather Forecasting over Iraq Using Machine Learning
In one sentence. Compares random forest, decision tree and gradient boosting for Iraq weather variables from NASA data; random forest reaches 92% accuracy.
Labels
- Topic
- Local & station forecasting
- Type
- Application study
- Method
- Classical ML (trees, GP, linear, kernels)
- Time scale
- 6 h–3 days
- Domain
- Regional
- Data
- Other
- Status
- Research
- Identifiers
- DOI:10.54216/jaim.020204 OpenAlex:W4366309794
- Added
- 2026-10-22
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