Rainfall Prediction: Accuracy Enhancement Using Machine Learning and Forecasting Techniques

Abstract

The paper is focused to provide the insights of climate to the clients from various businesses, e.g, agriculturists, researchers etc., to comprehend the significance of changes in climate and atmosphere parameters like precipitation, temperature, humidity etc. Precipitation estimate is one of the critical investigations in field of meteorological research. In order to predict precipitation, an endeavor is made to a couple of factual procedures and machine learning techniques to forecast and estimate meteorological parameters. For experimentation purpose daily observations were considered. The accuracy assessment of forecasting model experimentation is done using validation of results with ground truth. The experimentation demonstrates that for forecasting meteorological parameters ARIMA and Neural Network works best, and best classification accuracy in comparison to other machine learning algorithms for forecasting precipitation for next season was given by Random Forest model.