Earthquake destructive power prediction device and method based on recurrent neural network

A technology of cyclic neural network and prediction device, which is applied in the direction of measuring device, seismology, geophysical measurement, etc., can solve the problems of high efficiency, not satisfying real-time emergency, low efficiency, etc., and achieve the effect of accurate evaluation
CN110780347AActive Publication Date: 2020-02-11TSINGHUA UNIV

Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
TSINGHUA UNIV
Publication Date
2020-02-11

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Abstract

The invention discloses an earthquake destructive power prediction device and method based on a recurrent neural network. The device comprises a sensing module for obtaining information of a target object, a calculation and analysis module for providing resource (calculation power) support for analysis, a communication module for providing information transmission capability, and a display modulefor providing a result display platform. The sensing module is used to obtain seismic data of the target object; the calculation and analysis module is used to read and preprocess the seismic data; aneural network prediction model analyzes the preprocessed seismic data to generate an earthquake destructive power prediction result; the communication module sends the earthquake destructive power prediction result to a preset receiving end; and the display module carries out visual conversion on the earthquake destructive power prediction result, and displays the result by means of an electronicdisplay screen. Thus, destruction condition of the target object when confronting with the earthquake can be predicted accurately in real time, and the device and method have great significance in evacuation organization, earthquake early warning and the like.
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Description

technical field

[0001] The invention relates to the field of civil structural engineering and the technical field of disaster prevention and reduction, in particular to a device and method for predicting earthquake destructive force based on a cyclic neural network. Background technique

[0002] Earthquake disaster is an important security threat faced by buildings and one of the most serious casualties among various natural disasters. It is a factor that must be considered in building design and organizing personnel evacuation. When an earthquake disaster comes, it is of great significance to accurately and timely understand the earthquake damage suffered by the target area for organizing personnel evacuation and rescue and disaster relief. At present, there are two main ways to obtain earthquake destructive power: one is through field investigation or nonlinear time-history analysis, which is accurate but inefficient, and does not meet the real-time requirements of emergen...

Claims

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