Rainfall analysis and prediction using ensemble learning for Karnataka State
In one sentence. A stacking ensemble of machine learning models estimates annual rainfall for Karnataka state using 1901–2015 station records.
Abstract
Accurate prediction of rainfall can save farmers from crop damage as erratic rains in India have caused agricultural losses. Due to continuous climate change, rainfall and weather prediction has become essential. Rain causes damage to people and property. So, rainfall forecasting is crucial for crop as our country’s economy is still heavily dependent on agriculture. Using machine learning (ML) and deep learning (DL) models, we can train these models for the rainfall dataset and make predictions. In this paper, we estimate rainfall over the Karnataka region using a stacking ensemble model on a rainfall dataset collected between 1901 and 2015.
Labels
- Topic
- Local & station forecasting
- Type
- New model or method
- Method
- Classical ML (trees, GP, linear, kernels)
- Time scale
- Seasonal to annual
- Domain
- Local / station
- Data
- Station / in-situ
- Status
- Research
- Identifiers
- DOI:10.11591/ijeecs.v32.i2.pp1187-1198 OpenAlex:W4386995224
- Added
- 2026-10-22
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