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Tunnel surrounding rock geological classification information prediction method based on Bayesian neural network

A neural network and prediction method technology, applied in the field of rock tunnel engineering, can solve problems such as insufficient prediction accuracy, and achieve the effect of preventing geological disasters and improving prediction accuracy

Active Publication Date: 2021-03-19
SOUTHEAST UNIV
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Problems solved by technology

[0004] The invention provides a method for predicting geological classification information of surrounding rocks of tunnels based on Bayesian neural network, which solves the problem of insufficient prediction accuracy of existing prediction methods for geological classification information of surrounding rocks of tunnels

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  • Tunnel surrounding rock geological classification information prediction method based on Bayesian neural network
  • Tunnel surrounding rock geological classification information prediction method based on Bayesian neural network
  • Tunnel surrounding rock geological classification information prediction method based on Bayesian neural network

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Embodiment Construction

[0030] The present invention is described in further detail now in conjunction with accompanying drawing. These drawings are all simplified schematic diagrams, which only illustrate the basic structure of the present invention in a schematic manner, so they only show the configurations related to the present invention.

[0031] Analysis of the current situation of insufficient prediction accuracy of the prediction method for the geological classification information of the tunnel surrounding rock is due to the fact that when inferring the indicators of the geological classification information of the tunnel surrounding rock, the geological classification information of the similar tunnel surrounding rock is not considered, and the geological information itself is ignored Uncertainty will lead to the problem of insufficient precision of inference results. This application applies Bayesian neural network theory to the prediction of geological classification information of tunnel ...

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Abstract

The invention relates to a tunnel surrounding rock geological classification information prediction method based on a Bayesian neural network, and the method comprises the steps: collecting surrounding rock geological classification information of an existing tunnel and a fine collection tunnel under construction, carrying out the normalization processing, and determining the probability distribution of the tunnel surrounding rock geological classification information through Monte Carlo random analysis; preliminarily determining the number of nodes of an input layer, a hidden layer and an output layer of the Bayesian neural network model so as to establish a Bayesian neural network prediction model by utilizing the existing tunnel engineering data with similar geological information; andupdating the prediction model in real time by utilizing tunnel surrounding rock geological classification information newly obtained in the excavation process along with continuous forward advancing of the working face, and further gradually improving the prediction precision of the model. The prediction method provided by the invention has good universality and high prediction precision, can makeeffective judgment on geological classification information of an unknown section in front of tunnel excavation in advance, and is suitable for prediction of geological classification information ofmost tunnel surrounding rocks.

Description

technical field [0001] The invention relates to a method for predicting geological classification information of tunnel surrounding rock based on a Bayesian neural network, and belongs to the technical field of rock tunnel engineering. Background technique [0002] As an integral part of tunnel engineering, surrounding rock plays a decisive role in the entire life cycle from engineering design and construction to subsequent operation and maintenance. At present, the design of tunnel engineering is shifting from the traditional application of safety factor to a more reasonable design based on reliability, and the essence of reliability design requires the statistical characteristics of geological classification information of tunnel surrounding rock. Existing theoretical or practical methods seldom consider the uncertainty of geological classification information when evaluating the grade of tunnel surrounding rock; at the same time, during the tunnel excavation process, the ...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/04G06Q10/06G06F30/27G06N3/04G06N3/08G06N7/00G06F111/08
CPCG06Q10/04G06Q10/06393G06F30/27G06N3/08G06F2111/08G06N7/01G06N3/045
Inventor 张琦王宁李建春蒋擎何磊张宸浩马艳宁郑彦龙
Owner SOUTHEAST UNIV
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