Year: 2025
Type: article
Abstract: Rainfall Prediction is a tough undertaking due to erratic patterns of rainfall and climate fluctuations all throughout the world. Rainfall forecasts helps to prevent floods and even assists in agriculture for producing crops. Rainfall prediction is aided by machine learning, which uses previously recorded weather data to identify unknown trends. This paper predicts rainfall using a machine learning classification technique. Of the total data, 80% is the training data and 20% is the tested data. Analysis is done on the number of actual and expected forecasts. The accuracy of the employed classification model is found to be 85%. The accuracy of numerous different machine learning techniques is also compared.
Authors: Suraj B S Suraj B S, C Chethana C Chethana, Chetan kumar V, Sindhu B S Sindhu B S
Language: English
Subfield: Environmental Engineering
Field: Environmental Science
Domain: Physical Sciences
Open Access status: bronze
OpenAlex ID: W4407592190