A Prediction Method of Underground Earthquake Amplitude Parameters
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 implementation mode one: refer to figure 1 Specifically illustrate this embodiment, a kind of underground earthquake amplitude parameter prediction method described in this embodiment, comprises the following steps:
[0023] Step 1: Obtain underground and surface records, and establish an underground earthquake data set, and then use the magnitude, epicentral distance, station depth, surface amplitude parameters, quality factor, and soil layer shear wave velocity distribution as the input parameters of the deep neural network, The underground peak acceleration PUA, underground peak velocity PUV and underground peak plus displacement PUD are used as the output parameters of the deep neural network;
[0024] Step 2: Divide the earthquake data set into training set, verification set and test set according to the ratio of 8:1:1;
[0025] Step 3: First, normalize the input parameters to the range [0,1], then construct three deep neural network models based on PUA, ...
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