Study of California Earthquake Prediction Using Machine Learning Approach

Earthquake prediction is a highly challenging and complex task that has been the subject of scientific inquiry for many years. Even though we have learned a lot about earthquakes, it is still hard to predict them accurately and reliably. This is because earthquakes are complicated and hard to predict, and because our scientific knowledge and technology are not as advanced as they could be. There have been many ideas about how to predict earthquakes, such as using seismological and geophysical data,. But a lot of work still needs to be done to make a reliable and effective earthquake prediction system that can warn people in time and lessen the damage caused by earthquakes. In this work, an intelligent earthquake prediction model is developed using various machine learning algorithms. The seismological data of USGS is used for the model training and validation. The system has shown an prediction accuracy of 92.7%