Prediction of Earthquake Using Machine Learning Algorithms

Abstract

An earthquake is one of the most devastating natural catastrophes that may cause major infrastructure damage and casualties. Early earthquake detection can be crucial for minimizing damage and saving lives. Machine learning is a powerful tool that may be used to forecast earthquakes based on historical seismic data and other geographical data. This study examines the viability of predicting earthquakes using machine learning methods, especially the Random Forest Regressor and Neural Network Model. The purpose of this study is to make earthquake magnitude and depth predictions utilizing factors including time, place, and previous seismic activity data.

Topics & Concepts