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EMD-SVR-based ground surface settlement amount prediction method

A prediction method, a technology of land surface settlement, applied in the field of geotechnical engineering, can solve problems such as difficulty in meeting construction requirements, poor prediction accuracy and limitations of the model, and achieve the goal of improving generalization ability and learning performance, avoiding limitations, and improving prediction accuracy Effect

Active Publication Date: 2017-08-25
BEIJING UNIV OF TECH
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Problems solved by technology

[0003] At present, the commonly used methods include empirical method, numerical analysis method and measured data method, etc. However, some of the models may have poor prediction accuracy due to various factors such as lining form, construction conditions or complex stratum conditions, and it is difficult to meet the construction requirements. limit

Method used

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  • EMD-SVR-based ground surface settlement amount prediction method
  • EMD-SVR-based ground surface settlement amount prediction method
  • EMD-SVR-based ground surface settlement amount prediction method

Examples

Experimental program
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Effect test

Embodiment

[0062] The settlement monitoring data of DBZCZ-01-01 monitoring point at Changchun Ziyouda Road subway station is adopted. The monitoring time is from March 2014 to October 2014, which lasted 228 days. The measured settlement value curve is as follows figure 2 Shown.

[0063] (1) Select the first 190 periods of settlement monitoring data as the training sample set, and the last 38 periods as the test data set.

[0064] (2) Using empirical mode decomposition, the original sequence of the training sample set is divided into fluctuation items and trend items, as attached image 3 As shown, its accumulation from high frequency to low frequency is attached Figure 4 , Attached Figure 4 Among them, res is the trend component, and f2c5 is the fluctuation item obtained after accumulation.

[0065] (3) The five days before the target value output is selected as the input variable, and the sample set is To avoid blindly searching, the initialization range of model parameters (c, σ) is: c=[0,...

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Abstract

The invention discloses an EMD-SVR-based ground surface settlement amount prediction method. The method is an EMD, QPSO-SVR and ARIMA model-based ground surface settlement time sequence prediction method. A ground surface settlement actual measurement sequence is decomposed and reconstructed into a fluctuation component and a trend component by utilizing EMD; data is classified into two categories by adopting a sliding window method, wherein one part is used for model training and the other part is used for testing; then an ARIMA model and a QPSO-SVM model are built for analyzing the two components; and finally predicted values are subjected to summation, thereby obtaining a final predicted result. Compared with other settlement prediction methods, the method has the characteristics of high prediction precision, satisfied construction requirements and wide application range.

Description

Technical field [0001] The invention relates to the field of geotechnical engineering, in particular to a method for predicting surface settlement combining empirical mode decomposition, support vector regression and autoregressive moving average model. Background technique [0002] During the construction of the subway, the substantial surface settlement will have a serious impact on the nearby buildings and underground facilities. However, surface settlement is a complex process with multiple factors. Surface settlement varies due to unquantifiable factors such as soil conditions, groundwater level, and construction methods. For determining the potential risks of surrounding buildings, accurate prediction of future surface settlement can be Effectively prevent accidents caused by excessive settlement, ensure the normal progress of construction, and realize dynamic design and information construction. [0003] At present, the more commonly used methods include empirical method, n...

Claims

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Application Information

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IPC IPC(8): G06F17/50G06Q10/04G06Q50/08
CPCG06F30/20G06F2111/10G06Q10/04G06Q50/08
Inventor 李建更王朋飞姚爱军李立杰张岩
Owner BEIJING UNIV OF TECH
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