Ground subsidence prediction system and method based on support vector machine

A support vector machine and land subsidence technology, which is applied in database management systems, computer components, character and pattern recognition, etc., can solve problems affecting ground subsidence, poor fault tolerance, construction risks, etc., to ensure smooth operation and improve storage capacity , to avoid the effect of abnormal operation

Active Publication Date: 2017-09-12
XIDIAN UNIV
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  • Abstract
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  • Claims
  • Application Information

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Problems solved by technology

The traditional land subsidence analysis method is to train the model in stand-alone and serial mode. When faced with massive data, problems such as

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  • Ground subsidence prediction system and method based on support vector machine
  • Ground subsidence prediction system and method based on support vector machine
  • Ground subsidence prediction system and method based on support vector machine

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Embodiment 1

[0030] Shield construction needs to use machine operation data, construction geological data and construction environment data to predict the ground subsidence of the construction line. The traditional ground subsidence analysis method is to train the model in single machine and serial mode. When faced with massive data The exposed problems such as slow speed, low efficiency and poor fault tolerance directly affect the prediction accuracy of ground settlement, which in turn brings construction risks.

[0031] For this present situation and problem, the present invention launched research, proposed a kind of land subsidence prediction system based on support vector machine, see figure 1, comprising Hadoop big data analysis platform, data collection module, data preprocessing module, model construction module, subsidence prediction module in the land subsidence prediction system based on support vector machine of the present invention, data collection module, data preprocessing m...

Embodiment 2

[0034] The overall composition of the land subsidence prediction system based on support vector machine is the same as embodiment 1, see figure 1 , the data collection module of the present invention includes a data collection range determination sub-module and a data storage sub-module, the data collection range determination sub-module is to determine the characteristic variables through the mechanism analysis in the shield construction process, collect the corresponding machine operation data, and construct Geological data and construction environment data, and determine the characteristic data related to the settlement; the data storage sub-module of the data collection module is to store the collected land subsidence data, that is, the characteristic data, on the distributed file system of the Hadoop big data analysis platform .

Embodiment 3

[0036] The overall composition of the land subsidence prediction system based on support vector machine is the same as embodiment 1-2, see figure 1 , the data preprocessing module of the present invention includes a cleaning processing submodule, a denoising processing submodule, a normalization processing submodule and a dimensionality reduction processing submodule. The cleaning processing sub-module is to detect and fill the null values ​​in the original data, so as to avoid abnormalities caused by missing data when building the model. The denoising processing sub-module is to eliminate the abnormal points in the data processed by the cleaning processing sub-module, so as to reduce the influence of "noise" data on the model accuracy. The normalization processing sub-module is to map the data processed by the cleaning processing sub-module and denoising processing sub-module to the [0,1] interval, eliminating the dimensional impact caused by the inconsistency of data units b...

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Abstract

The invention discloses a ground subsidence prediction system and a method based on a support vector machine, which are mainly used to the problem that the supporting system cannot satisfy the demand for analysis of mass data in the process of shield construction. The system comprises a Hadoop big data analysis platform, a data collection module, a data preprocessing module, a model building module, and a subsidence prediction module. In the prediction method, for de-noising in preprocessing, a clustering algorithm based on confidence interval estimation and the Pauta criterion is proposed for abnormal point detection. In prediction model building, the iterative calculation process of the weight vector is updated with the average value of N partitions, which, together with stochastic gradient descent, enhances the training speed. The system has the ability to store and analyze mass data and the ability of high-performance redundancy. Real-time and efficient data analysis is realized. The system and the method are used for ground subsidence prediction in the process of shield construction to provide reference and adjustment basis for project managers and construction operators.

Description

technical field [0001] The invention belongs to the technical field of industrial big data, and in particular relates to ground subsidence prediction in the field of subway shield tunneling construction, specifically a support vector machine-based ground subsidence prediction system and method, which can be used to predict the amount of ground subsidence during shield tunneling construction . Background technique [0002] Urbanization is an important part of my country's infrastructure. In recent years, with the development of the economy, the process of urbanization in my country has been accelerating, the development and utilization of urban underground space has developed rapidly, and a large number of tunnel engineering projects have been produced. Underground engineering represented by the shield construction method has become the mainstay of urban underground construction. Way. [0003] The so-called ground subsidence prediction refers to the prediction of the degree ...

Claims

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Application Information

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IPC IPC(8): G06K9/62G06F17/30
CPCG06F16/182G06F16/25G06F18/2411
Inventor 孔宪光常建涛王佩冯尓磊刘尧
Owner XIDIAN UNIV
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