The Application of Machine Learning in Determining Earthquake Magnitude as an Early Warning

Abstract

Since ancient times, earthquake disasters have always been one of the most harmful natural disasters, and it is necessary to reduce the damage caused by earthquakes effectively. The earthquake early warning is a new technology that has been gradually mature in recent years and can effectively reduce earthquake disasters. The ability to accurately and quickly predict the earthquake magnitude has become an important but difficult part of the earthquake early warning technology. Currently, many countries in the world have been engaged in the projects of establishing and improving the system of earthquake early warning, and completed two methods to predict the earthquake magnitude as a kind of earthquake early warning, namely, the method of characteristic frequency and the method of characteristic amplitude. In recent years, with the constant improvement of deep learning, the application of machine learning in determining the earthquake magnitude as an early warning has been showing great development prospects and application possibility.