Short-term rainfall prédiction using prédictive analytics: A case study in Telangana

Abstract

Rainfall forecasting is critical because heavy rains can bring a full of tragedies. This prediction aids people in requiring preventive steps, and it should be correct. There are two types of rainfall forecasting: short-term forecasting and long-term forecasting. Predictions are typically correct for short-term, but creating a model for future rainfall prediction is the most difficult task. Because it is strongly tied to economy and human lives, heavy precipitation forecast could be a severe disadvantage for natural science departments. It’s the cause of natural disasters like floods and droughts that affect people all around the world every year. For countries like India, where agriculture is the primary source of income, the accuracy of rainfall estimates is critical. Regression may be used in the prediction of precipitation utilizing machine learning approaches. The goal of this work is to provide non-experts with easy access to the techniques and approaches used in the field of precipitation prediction, as well as a comparison of the various machine learning algorithms.