Prediction of Rainfall using Machine Learning algorithms

Computer Science and Engineering

One of the pillars of the Indian economy is the agricultural sector. Even while rainfall is crucial for farmers, predicting it has become a huge challenge in recent years. If farmers can accurately estimate when it will rain, they may better plan their crops and avoid problems. Alterations to the weather are being hastened by global warming, which is having devastating effects on both humans and the natural world. Because of the warming air and rising sea levels, floods are becoming more common and drought is becoming more common in farmed fields. Bad climate change causes excessive rainfall that is neither seasonal nor appropriate. The ability to forecast precipitation is a powerful tool for understanding weather patterns. The overarching goal of this research is to help clients in the agricultural, research, and power generation sectors, among others, understand the importance of climate change and the parameters that influence it, such as temperature, humidity, precipitation, wind speed, and rainfall projections. It is difficult to forecast rainfall because it is also dependent on geographic regions. Machine learning, a dynamic branch of artificial intelligence, aids in weather prediction. In order to forecast the weather, this study will use a dataset with several attributes from the UCI repository. Building a more accurate method for predicting rainfall using Machine Learning classification algorithms is the primary goal of this research.

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