Membrane bag sand bank slope settlement prediction method and system based on neural network

By integrating construction parameters and geological data using neural network technology, the settlement and risks of membrane bag sand embankment slopes are analyzed, solving the problem of inaccurate settlement prediction in existing technologies. This achieves more accurate settlement prediction and risk assessment, ensuring project safety.

CN121980191AInactive Publication Date: 2026-05-05GUANGDONG OCEAN UNIVERSITY +1
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Patent Information

Application Number
CN202610222107.3
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2026-02-25
Publication Date
2026-05-05
Estimated Expiration
Not applicable · inactive patent

AI Technical Summary

Technical Problem

Existing technologies fail to fully consider the impact of the foundation structure on the settlement of the membrane bag sand embankment slope, resulting in inaccurate predictions that cannot effectively support slope reinforcement and construction rate adjustments.

Method used

A neural network-based approach is used to acquire construction parameters, foundation monitoring data, and geological exploration data. Feature fusion and prediction model analysis are performed, and a dynamic early warning mechanism is combined to identify settlement anomaly risks and output settlement prediction results and risk levels.

Benefits of technology

It improves the accuracy and reliability of predicting settlement of membrane bag sand embankment slopes, provides effective data support for embankment reinforcement and construction adjustment, and enhances project safety and risk control capabilities.

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Abstract

The invention discloses a membrane bag sand levee slope settlement prediction method and system based on a neural network, and belongs to the technical field of prediction systems.The method comprises the steps that construction parameters, foundation monitoring data and geological exploration data of a membrane bag sand levee slope are obtained; performing feature fusion by analyzing correlation between the construction parameters and the compression amount of each foundation soil layer in the time dimension and between the foundation monitoring data and the compression amount of each foundation soil layer to obtain fusion time sequence features; and on the basis of the geological exploration data, using a settlement prediction model and fusion time sequence characteristics, predicting each compression amount by analyzing the pore drainage rate of each foundation soil layer, outputting a settlement prediction result of the membrane bag sand bank slope, identifying the settlement abnormal risk of the membrane bag sand bank slope, and outputting the settlement risk grade of a preset construction point. Therefore, by implementing the method and the device, the problem that the predicted total settlement amount of the film bag sand bank slope is not accurate enough due to the fact that the influence of the bank slope foundation structure on the settlement amount in the construction process is not completely considered in the prior art can be solved.
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