Underground seismic oscillation amplitude parameter prediction method
A prediction method and ground motion technology, applied in neural learning methods, special data processing applications, biological neural network models, etc., can solve the problem of lack of ground motion amplitude variation along the depth and so on.
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[0022] Specific embodiment one: reference figure 1 To describe this embodiment in detail, the method for predicting the amplitude parameter of underground ground motion described in this embodiment includes the following steps:
[0023] Step 1: Obtain underground and surface records, and establish an underground ground motion data set, and then use the magnitude, epicenter distance, station depth, surface amplitude parameters, quality factors and soil shear wave velocity distribution as input parameters of the deep neural network. Take underground peak acceleration PUA, underground peak velocity PUV and underground peak plus displacement PUD as the output parameters of the deep neural network;
[0024] Step 2: Divide the ground motion data set into training set, verification set and test set according to the ratio of 8:1:1;
[0025] Step 3: First standardize the input parameters to the range of [0,1], then construct three deep neural network models based on PUA, PUV and PUD, and use ...
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