Method and system for identifying finite fault fracture parameters of earthquake
A fault, limited technology, applied in the field of earthquake monitoring, which can solve problems such as high computational complexity and long computational time
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[0029] In order to make the purpose, technical solutions and advantages of the present disclosure clearer, the present disclosure will be further described in detail below in conjunction with specific embodiments and with reference to the accompanying drawings.
[0030] We propose a method based on deep convolutional neural networks to quickly identify earthquake-finite fault rupture parameters. Convolution Neural Network (CNN) is a feed-forward neural network that starts from the input layer and advances layer by layer. Each layer receives the previous layer as input and outputs to the next layer until the end. The output layer of the network is a directed acyclic network. A deep convolutional neural network means that there are many convolutional layers between the input layer and the output layer. Deep convolutional neural networks have excellent performance in computer vision and natural language processing. Here, we will apply the powerful image recognition capabilities...
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