CLASSIFICATION AND RECOGNITION OF NATURAL EARTHQUAKES AND BLASTS BASED ON CONVOLUTIONAL NEURAL NETWORKS
In order to quickly and efficiently classify and identify natural and non natural earthquakes,this pa-per uses 302 natural earthquakes and 308 non natural earthquake events such as blasting,collapse,and dy-namic compaction recorded by seismic stations in Yunnan Province and surrounding areas as the test and train-ing data of the neural network model.A VGG19 convolutional neural network model is designed to identify and classify natural and non natural earthquakes.The results show that the recognition accuracy of VGG19 on the training and testing sets is over 92％,and the recognition accuracy of natural earthquakes is about 96％;The recognition accuracy of non natural earthquakes is about 98％.Through experiments,it has been demonstrated that the VGG19 neural network model has practical significance for identifying natural and non natural earth-quakes.
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万方数据
