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Landslide prediction method and system

A forecasting method and forecasting device technology, applied in the direction of instruments, design optimization/simulation, calculation, etc., can solve the problems of low automation, low efficiency, low forecasting accuracy, etc., and achieve the effect of improving forecasting efficiency and forecasting accuracy

Active Publication Date: 2019-05-21
SHENZHEN UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

It can be seen that the current landslide prediction method is not only low in automation and low in efficiency, but also may have low prediction accuracy due to subjective factors.

Method used

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  • Landslide prediction method and system
  • Landslide prediction method and system
  • Landslide prediction method and system

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Embodiment 1

[0054] see figure 1 , figure 1 It is a schematic flowchart of a landslide prediction method disclosed in an embodiment of the present invention. in, figure 1 The described landslide prediction method based on the random forest model can be applied to a terminal device for monitoring the movement state of landslides, which is not limited in the embodiments of the present invention. Such as figure 1 As shown, the landslide prediction method based on the random forest model may include the following steps:

[0055] 101. Collect multiple types of landslide training data, and respectively construct landslide early warning and classification perspectives for the multiple types of landslide training data.

[0056] In the embodiment of the present invention, the above-mentioned landslide training data includes sensor displacement training data, marker movement trajectory training data, and crack size training data, which is not limited in the embodiment of the present invention. ...

Embodiment 2

[0104] see figure 2 , figure 2 It is a structural schematic diagram of a landslide prediction device disclosed in an embodiment of the present invention. in, figure 2 The described landslide prediction device based on the random forest model is a terminal device for monitoring the movement state of landslides, which is not limited in the embodiments of the present invention. Such as figure 2 As shown, the landslide prediction device based on the random forest model includes an acquisition module 401, a first building module 402, a second building module 403, an evaluation module 404 and a fusion module 404, wherein:

[0105] The collecting module 401 is used for collecting multi-type landslide training data.

[0106] In the embodiment of the present invention, the landslide training data includes at least one of sensor displacement training data, marker movement track training data, and crack size training data, which is not limited in this embodiment of the present in...

Embodiment 3

[0124] see Figure 4 , Figure 4 It is a structural schematic diagram of another landslide prediction device disclosed in the embodiment of the present invention. Such as Figure 4 Shown, this landslide prediction device based on random forest model can comprise:

[0125] A memory 401 storing executable program codes;

[0126] a processor 402 coupled to the memory 401;

[0127] The processor 402 invokes the executable program code stored in the memory 401 to execute the steps in the landslide prediction method based on the random forest model described in the first embodiment.

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Abstract

The invention discloses a landslide prediction method and device, and the method comprises the steps: collecting multiple types of landslide training data, and building a landslide early warning classification view angle for each type of landslide training data; constructing a multi-view-angle weight random forest model for all landslide early warning classification view angles by using the randomforest model; collecting multiple types of landslide test data, and respectively constructing landslide observation view angles aiming at each type of landslide test data; and using the multi-view weight random forest model to perform model evaluation on each landslide observation view angle to obtain a model evaluation result, and fusing the model evaluation result to obtain a landslide early warning classification result. Visibly, by implementing the method, the landslide change condition can be analyzed through the multi-view weight random forest model, the prediction efficiency and prediction accuracy of the landslide motion state can be improved, and a quantitative evaluation basis can be provided for landslide stability analysis and evaluation, prediction and early warning of landslide and later prevention and control work in the later period.

Description

technical field [0001] The invention relates to the technical field of landslide prediction, in particular to a landslide prediction method and system. Background technique [0002] Landslide is a common geological disaster that occurs in nature. It is extremely harmful and often causes great losses to people's lives and property. As we all know, the prediction of landslides is not the result of subjective guesswork. It needs to be based on the real-time deformation monitoring of landslides. Reasonable predictions. At present, landslide prediction methods mainly include engineering condition analysis, site condition analysis, rock and soil mechanics experiment, and mechanical model. However, it has been found in practice that the current landslide prediction methods usually carry out detailed off-the-shelf engineering geological surveys first, establish geological models, then take samples to conduct mechanical tests in the laboratory or on site, further establish mechanic...

Claims

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Application Information

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IPC IPC(8): G06F17/50
CPCG06F30/20
Inventor 李岩山周李夏荣杰刘瑜王海鹏谢维信
Owner SHENZHEN UNIV
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