Study on Earthquake Prediction Model Based on Traffic Disaster Data

This paper collects data on the damage to the traffic system caused by earthquakes in China in the past two decades, and uses KNN algorithm, SVM algorithm, logistic regression algorithm, naive Bayes algorithm and decision tree algorithm to train the data, then establish earthquake prediction models. The paper introduces the process of preprocessing, modelling, evaluation, and visualization of disaster data. An earthquake disaster inversion model based on traffic data has been established, which can predict the earthquake intensity based on the relevant data provided by the traffic department. The prediction accuracy is relatively accurate, which is very helpful for earthquake prediction and rescue operations.