Landslide displacement prediction method based on wavelet transform-rough set-support vector regression (WT-RS-SVR) combination

A technology of WT-RS-SVR, prediction method, applied in the test of infrastructure, infrastructure engineering, construction, etc.

Inactive Publication Date: 2016-01-13
CHINA UNIV OF GEOSCIENCES (WUHAN)
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Problems solved by technology

Therefore, this area urgently needs to provide a kind of method that landslide displacement is decomposed into different parts according to different influencing factors, and adopts comprehensive composite model to carry out landslide displacement prediction, and this method is the effective means of processing landslide deformation curve, but this area There is currently no such method in s

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  • Landslide displacement prediction method based on wavelet transform-rough set-support vector regression (WT-RS-SVR) combination

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[0022] The present invention will be described in detail below in conjunction with specific examples, but the protection scope of the present invention is not limited to the following examples.

[0023] The landslide displacement prediction method based on the combination of WT-RS-SVR provided by the present invention is as follows: figure 1 described, including the following steps:

[0024] First of all, it is necessary to collect all relevant inducing factors related to the location of the target landslide, analyze the characteristics of the landslide, and find out all the factors that affect the displacement of the landslide. The above-mentioned inducing factors include topography, stratum lithology, geological structure, hydrogeological conditions, and climate , rainfall and human engineering activities.

[0025] (1) Wavelet decomposition: collect the displacement monitoring data of the target landslide, select representative and typical displacement monitoring points, dr...

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Abstract

The invention provides a landslide displacement prediction method based on wavelet transform-rough set-support vector regression (WT-RS-SVR) combination. By means of the method, according to the characteristics of the influence factors of landslide displacement, the complex displacement process and landslide displacement monitor data measured in real time, accumulative displacement of a typical monitor point is decomposed into trend-term displacement and periodic-term displacement through WT, and a trend-term displacement prediction function is obtained through curve fitting; screening is conducted on the influence factors of the landslide displacement through an RS algorithm, and selected factor sets are used as input factor sets of an SVR machine, accordingly a landslide displacement optimization prediction model based on WT-RS-SVR combination is established, and the precision of a prediction result is analyzed and evaluated. The prediction result of the landslide displacement prediction method can well embody the development and change tendency of the landslide displacement. The landslide displacement prediction method has high prediction capacity, and is accurate, effective and practical.

Description

technical field [0001] The invention provides a new landslide displacement prediction method based on the combination of wavelet transform, rough set and support vector regression machine, which belongs to the field of environmental protection. Background technique [0002] Landslide is a serious geological hazard, and its deformation evolution process is affected by both controlling and influencing factors of landslide. In the process of deformation evolution, the landslide deformation displacement will present a corresponding step-like change feature under the influence of internal and external factors. In actual landslide forecasting, if the landslide deformation is analyzed and predicted directly based on the landslide cumulative displacement curve, it is easy to make a wrong judgment on the landslide. Therefore, this area urgently needs to provide a kind of method that landslide displacement is decomposed into different parts according to different influencing factors,...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): E02D33/00
Inventor 胡友健张凯翔牛瑞卿
Owner CHINA UNIV OF GEOSCIENCES (WUHAN)
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