paper
2023
Local & station forecasting
New model or method
Classical ML (trees, GP, linear, kernels)6 h–3 days Journal
2023-01-01
004
Jan 2023
T. Benil, P. Krishna Kumar, R. Bharathi
International Journal of Global Warming
Proposes an optimal KNN with data pruning for missing values to classify Seattle rainfall; reports better accuracy and lower runtime. Weakly described and narrow.
Efficient data pruning using optimal KNN for weather forecasting in cloud computing
In one sentence. Proposes an optimal KNN with data pruning for missing values to classify Seattle rainfall; reports better accuracy and lower runtime. Weakly described and narrow.
Labels
- Topic
- Local & station forecasting
- 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:10.1504/ijgw.2023.130984 OpenAlex:W4377081950
- Added
- 2026-10-22
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