This article provides an overview of deep learning methods and their application in earthquake monitoring and prediction.It introduces mainstream methods such as feedforward neural networks,convolutional neural networks,recurrent neural networks,transformer networks,autoencoders,generative adversarial networks,and deep rein-forcement learning networks.The article summarizes their application in phase picking,phase correlation,event detection,earthquake location,signal and event classification,and earthquake prediction.It also discusses the progress,advantages,challenges,and future directions of deep learning in earthquake monitoring and predic-tion.This summary serves as a valuable reference for applying deep learning in earthquake monitoring and predic-tion.
关键词
深度学习/监测预报/地震检测/地震定位/地震预测
Key words
deep learning/seismic monitoring and prediction/earthquake detection/earthquake location/seismic forecasting
维普
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