Application of AI Algorithms in Earthquake Detection and Location

With the development of seismic observation technology, the use of dense seismic network and large-scale seismic array has been widely valued. Consequently, the seismic waveform data has increased sharply. The traditional methods rely on artificial work to recognize seismic phase and locate the earthquakes. It is very low efficiency and time-consuming. The paper makes a comparison of the commonly used long and short time window, variance-based AIC method, template matching filter cross-correlation method, etc. And the limitations of these methods restrict the applications in the huge amount of seismic data. The latest development of micro-earthquake detection methods based on machine learning and artificial intelligence provides great convenience.