Rainfall Prediction Using Regression Analysis: Review Study of Democratic Republic of the Congo

Abstract

Meteorological scientists are continually looking for ways to better comprehend the Earth's atmosphere and construct accurate weather prediction models. Weather prediction has employed a variety of methodologies. Recently, machine learning algorithms have been frequently adopted as an alternative to traditional methods for weather prediction since they are thought to be more accurate. The rainfall rate is an important phenomenon in the weather system that has a direct impact on the agricultural and biological sectors. Accurate rainfall prediction plays a crucial role in various domains such as agriculture, water resource management, urban planning and many more. The purpose of this work is to develop a multiple linear regression model to forecast the rate of precipitation of Kinshasa city of Democratic Republic of the Congo.