Weather Forecast using Learning Vector Quantization Methods
In one sentence. Learning vector quantization neural network for weather forecasting reaches 72% accuracy; a small, locally scoped study with limited novelty.
Abstract
Weather forecasting is one of the important factors in daily life, as it can affect the activities carried out by the community. The study was conducted to optimize weather forecasts using artificial neural network methods. The artificial neural network used is a learning vector quantization (LVQ) method, in which artificial neural networks based on previous research are suitable for prediction. The research is modeling weather forecast optimization using the LVQ method. Models with the best accuracy can be used in terms of weather forecasts. Based on the results of the training that has been done in this study produces the best accuracy on the LVQ method which is to produce 72%.
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
- Other
- Status
- Research
- Identifiers
- DOI:10.21070/pssh.v1i.22 OpenAlex:W3167352788
- Added
- 2026-10-22
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