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 endeavour 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.