paper
2022
Local & station forecasting
Applications & impacts New model or method
Classical ML (trees, GP, linear, kernels)6 h–3 days Journal
2022-03-17
008
Mar 2022
Ala' Fathi Khalifeh, Abdullah Yousef Al-Qammaz, Laith Abualigah et al.
Journal of Intelligent & Fuzzy Systems
SSA-tuned least-squares SVM forecasts Amman temperature, pressure and soil humidity 24 to 72 h ahead for smart irrigation; a single-city study.
A machine learning-based weather prediction model and its application on smart irrigation
In one sentence. SSA-tuned least-squares SVM forecasts Amman temperature, pressure and soil humidity 24 to 72 h ahead for smart irrigation; a single-city study.
Labels
- Topic
- Local & station forecasting, Applications & impacts
- Type
- New model or method
- Method
- Classical ML (trees, GP, linear, kernels)
- Time scale
- 6 h–3 days
- Domain
- Local / station
- Data
- Station / in-situ
- Status
- Research
- Identifiers
- DOI:10.3233/jifs-219284 OpenAlex:W4220966645
- Added
- 2026-10-22
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