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Landslide displacement prediction method of hybrid machine learning model

A machine learning model and prediction method technology, applied in the field of computer mathematics, can solve problems such as low data usage, long modeling cycle, and data waste, and achieve the effects of improving credibility, shortening time period, and avoiding waste

Active Publication Date: 2019-07-09
GUILIN UNIV OF ELECTRONIC TECH +1
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Problems solved by technology

[0004] At present, the traditional landslide displacement prediction method adopts the prediction model to establish complex mechanical equations and statistical models according to the geological environment, which requires a large amount of calculation and a long modeling period. At the same time, with the development of technology, the data information obtained is increasing. Low data usage leads to a lot of data waste

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  • Landslide displacement prediction method of hybrid machine learning model
  • Landslide displacement prediction method of hybrid machine learning model
  • Landslide displacement prediction method of hybrid machine learning model

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Embodiment

[0027] like figure 1 As shown, a hybrid machine learning model landslide displacement prediction method, including the following steps:

[0028] S1. Obtain N groups of landslide displacement data from the landslide mountain displacement monitoring points and influencing factor sensors, and preprocess the N groups of landslide displacement data; specifically, the landslide displacement monitoring points are arranged as three vertical and one horizontal observation networks to make the measured landslide displacement The data can fully represent the characteristics and trends of landslides. The sensors mainly include the measurement data of reservoir water level and rainfall. According to the principle of time series analysis, wavelet de-drying processing is carried out;

[0029] S2. Decompose the preprocessed N groups of landslide displacement data into N groups of trend items and N groups of periodic items using the Hodrick-Prescott filter. N groups of trend items include N gr...

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Abstract

The invention discloses a landslide displacement prediction method of a hybrid machine learning model. Landslide influence factor mining and landslide displacement data acquisition and preprocessing are carried out on landslide monitoring points, and the landslide influence factor mining and landslide displacement data acquisition and preprocessing are used as training data of the model.The obtained landslide influence factors and landslide displacement data are regarded as a time sequence to be subjected to wavelet denoising processing.Based on a time sequence principle, a Hodrick-Prescott filter (HP) is used to decompose the landslide influencing factors and displacement data into trend and period terms. As for trend and the periodic terms, displacement prediction is carried out by using a second-order exponential smoothing (DBS) method and a dynamic multi-group particle swarm optimization (DMS-PSO) optimization extreme learning machine (ELM) model. Finally, the predicted period term displacement and the trend term displacement are added to obtain the total landslide prediction displacement. Aglobal optimal solution can be better solved through the periodic item displacement prediction model, so that the prediction precision and reliability are higher.

Description

technical field [0001] The invention relates to the field of computer mathematics, in particular to a method for predicting landslide displacement using a hybrid machine learning model. Background technique [0002] Landslide is a common geological disaster. It refers to the rock and soil on the slope, affected by internal and external factors such as groundwater, rainfall, earthquakes, human industry and daily activities, under the action of gravity, along the through shear failure. It is a natural phenomenon that slides down the slope as a whole or scatteredly. Frequent catastrophic accidents caused by landslides have brought huge hidden dangers to the safety of human life and property. It is of great significance to strengthen the related research on landslide prevention and treatment. The research on landslide displacement prediction is related to the site selection of many projects and the safety of life and property of surrounding residents; landslide prediction can w...

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Application Information

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IPC IPC(8): G06F17/50
CPCG06F30/20
Inventor 关善文邓洪高周李纪元法罗笑南
Owner GUILIN UNIV OF ELECTRONIC TECH