paper
2019
Local & station forecasting
New model or method
Classical ML (trees, GP, linear, kernels) Journal
2019-08-30
004
Aug 2019
S. Sheik Mohideen Shah*, Sathiskumar Meganathan, A. Kamali
International Journal of Engineering and Advanced Technology
Feed-forward neural network predicts rainfall from time series for agriculture and drought or flood warning, with no quantitative results given.
Soft Computing Research For Weather Prediction Using Multilayer Architecture
In one sentence. Feed-forward neural network predicts rainfall from time series for agriculture and drought or flood warning, with no quantitative results given.
Abstract
Rainfall prediction is helpful for the agriculture sector. Early prediction of drought and torrent situations is achieved through time series data. For the precise prediction, Artificial Neural Network(ANN) technique is used. The rainy dataset is tested using Feed Forward Neural Network(FFNN). The performance of this model is evaluated using Mean Square Error(MSE) and Magnitude of Relative Error(MRE). Better performance achieved when compared with other data mining techniques.
Labels
- Topic
- Local & station forecasting
- Type
- New model or method
- Method
- Classical ML (trees, GP, linear, kernels)
- Domain
- Local / station
- Data
- Station / in-situ
- Status
- Research
- Identifiers
- DOI:10.35940/ijeat.f9390.088619 OpenAlex:W4212766393
- Added
- 2026-10-22
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