Advancing Natural Disaster Prediction and Mitigation through Machine Learning Techniques

Abstract

This paper explores the application of machine learning (ML) techniques in predicting and mitigating the impacts of natural disasters. It reviews various ML models and their effectiveness in forecasting events such as earthquakes, hurricanes, floods, and wildfires. By examining the strengths and limitations of these techniques, the paper aims to highlight how ML can enhance disaster preparedness and response strategies.