Abstract
Rainfall forecasting is very challenging due to its uncertain nature and dynamic climate change. It's always been a challenging task for meteorologists. In various papers for rainfall prediction, different Data Mining and Machine Learning (ML) techniques have been used. These techniques show better predictive accuracy. A deep learning approach has been used in this study to analyze the rainfall data of the Karnataka Subdivision. Three deep learning methods have been used for prediction such as Artificial Neural Network (ANN) - Feed Forward Neural Network, Simple Recurrent Neural Network (RNN), and the Long Short-Term Memory (LSTM) optimized RNN Technique. In this paper, a comparative study of these three techniques for monthly rainfall prediction has been given and the prediction performance of these three techniques has been evaluated using the Mean Absolute Percentage Error (MAPE%) and a Root Mean Squared Error (RMSE%). The results show that the LSTM Model shows better performance as compared to ANN and RNN for Prediction. The LSTM model shows better performance with mini-mum Mean Absolute Percentage Error (MAPE%) and Root Mean Squared Error (RMSE%).
Highlights
Rainfall Prediction will always help to make decisions on agriculture, fisheries, forestry, tourism, etc
The results of the Artificial Neural Network (ANN)-Feed Forward Neural Network (FFNN) (Feed-Forward Neural Network) and Recurrent Neural Network (RNN) model were compared with the performance of Long Short-Term Memory (LSTM)
Performance of Hybrid Neural Network (HNN) in terms of F-measure, accuracy, precision, and recall compared with Multilayer Perceptron-Feedforward Neural Network (MLP-FFN)
Summary
Rainfall Prediction will always help to make decisions on agriculture, fisheries, forestry, tourism, etc. Monsoon plays a significant role in agriculture production. For countries like India, where agricultural production has been one of the main factors affecting the economy of India, a decent amount of rainfall gives the entire country an economic outlook and boosts the economy. A decent amount of rain enhances crop productivity and increases water resources. Where an excess amount of rainfall brings a flood, which destroys crops, causes structural damage, threatens human life. In India, floods occurred in 2019 due to excessive rainfall in July and August, which had affected 13 states, Karnataka and Maharashtra were the most
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