Roadway surrounding rock deformation predicting method based on neural network
A technology of neural network and surrounding rock deformation, applied in biological neural network models, special data processing applications, instruments, etc., can solve problems such as the maximum plastic zone damage depth, and achieve the effect of improving calculation efficiency
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[0028] In this prediction method, the key influencing factors of the surrounding rock are obtained through hierarchical analysis, the BP neural network model is established, and the training samples formed by the data groups obtained from the previous monitoring under different geological conditions are input. The data structure is a multidimensional matrix, and the training sample data is passed through trainlm The function trains the neural network system; the trained neural network is used to predict the initial deformation of the roadway excavation, and according to the input index parameters, the settlement of the surrounding rock roof, the displacement of the bottom plate, the displacement of the side of the roadway and the generated The maximum damage depth in the plastic zone, the neural network will predict the roadway deformation at the initial stage of excavation according to the prediction request, select appropriate support parameters to control the roadway support,...
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