Rainfall prediction through TRMM dataset using machine learning model

Abstract

In our world, rainfall forecasting is extremely important. Agriculture is seen as the primary source of revenue for the economy. A proper estimate of rainfall is needed to make proper agricultural investments. Rainfall forecasting is needed for people living in coastal areas, in addition to agriculture. People living by the coast are at a higher risk of heavy rain and flooding, so they should be aware of the weather forecast well in advance so that they can schedule their stay accordingly. We use a machine-learning algorithm to predict rainfall for this reason. Machine Learning algorithm used is Linear Regression. In linear regression, to predict the dependent variable (rainfall) using an independent variable (soil moisture). A comparison of two machine learning algorithms reveals which is more effective.