RANDOM FOREST IN FORECASTING RAIN-INDUCED LANDSLIDES

In our recent conducted study, the researchers venture on the significant application of the random forest model for forecasting rain-induced landslides in the Philippines. The result of the research shows that the combination of rainfall and environmental variables can achieve an impressive high accuracy of 90%. This study highlights the potential of using machine learning model for effective early warning systems in vulnerable regions such as the mountainous places. We, the researchers, invite you to check out the paper for further insights and discussion!