EARTHQUAKE PREDICTION USING MACHINE LEARNING

An earthquake is a natural calamity that is well-known for the devastation it causes to both naturally existent and artificial structures, including as buildings and residential areas.Seismometers are used to measure earthquakes because they detect vibrations induced by seismic waves travelling through the earth's crust.To forecast earthquakes, an examination of current machine learning classifier approaches is employed.Machine learning algorithms such as Logistic Regression, Support Vector Machine (SVM), Random Forest Classifier, and K-Nearest Neighbours,decision tree are used to forecast earthquakes.After examining all of the previously utilised methods, the best algorithm will be considered.The method used to forecast the property will be investigated,as will the data analysis.