Disaster Prediction Using Appropriate Machine Learning Techniques
Aishwarya Bangar, Shubhan Ansari, Sumer Shahed Ali, Visharad Baderao, Bhagyashree Alhat · 2024
This paper provides the insights of disaster forecasting methods, focusing on the strengths, limitations, and applications of other models and ideas to predicting natural disasters. Disasters and pandemics are most unlikely events which concerns many nations. Till date multiple ways are used to detect or predict natural disasters. Various machine learning techniques are used in detecting, preventing or mitigating disasters. We focus on predicting natural disasters beforehand to reduce its effects using XGBoost algorithm. The study shows the challenges of accurate forecasting and early warning systems.The paper also highlights about user friendly and interactive integrated website for disaster prediction. The paper gives the overview of the successful development and implementation of various models to predict earthquake, tsunami, flood and landslide.