Tunnel leakage rate prediction method based on neural network
A prediction method and neural network technology, applied in the direction of neural learning method, biological neural network model, neural architecture, etc., can solve problems such as tunnel structure safety risk prediction, leakage rate prediction and analysis, etc., to achieve rich results and operational efficiency high effect
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[0026] based on the following Figure 1 ~ Figure 3 , specifically explain the preferred embodiment of the present invention.
[0027] Such as figure 1 As shown, the present invention provides a neural network-based tunnel leakage rate prediction method, comprising the following steps:
[0028] Step S1, collecting tunnel images related to the flow rate of seepage water to form a data set, the data set includes a training data set, a test data set, and a prediction data set;
[0029] Step S2, constructing a tunnel leakage rate prediction model based on a convolutional neural network and a long-short-term memory network;
[0030] Step S3, using the training data set and the test data set to train the tunnel leakage rate prediction model;
[0031] Step S4. Input the prediction data set into the trained tunnel leakage rate prediction model to obtain the leakage water velocity corresponding to the tunnel image.
[0032] Further, the method for collecting data sets includes:
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