Study of landslide deformation prediction based on gray model-evolutionary neural network model considering function of environmental variables

CAO Yang-bing; YAN E-chuan; XIE Liang-fu

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Study of landslide deformation prediction based on gray model-evolutionary neural network model considering function of environmental variables

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- Study of landslide deformation prediction based on gray model-evolutionary neural network model considering function of environmental variables
- Vol. 33, Issue 3, (2012)
- 作者机构：
  
  中国地质大学（武汉）工程学院,武汉,430074
- 作者简介：
- 基金信息：
- DOI：
  CLC： TV698
- Online First：12 March 2012，
  
  Published：2012
- 稿件说明：
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CAO Yang-bing, YAN E-chuan, XIE Liang-fu. Study of landslide deformation prediction based on gray model-evolutionary neural network model considering function of environmental variables[J]. 2012, 33(3).
DOI：

CAO Yang-bing, YAN E-chuan, XIE Liang-fu. Study of landslide deformation prediction based on gray model-evolutionary neural network model considering function of environmental variables[J]. 2012, 33(3). DOI：

摘要

滑坡变形预测对于指导灾害的预防工作、保护人民的生命和财产安全具有重大实用价值。从系统论观点出发，结合岩土体流变理论和时序分析原理，在深入研究影响滑坡变形的主控环境变量基础上，将位移时序分解为趋势项和偏离项。采用灰色系统模型提取位移时序趋势项，结合遗传算法和人工神经网络建立起进化神经网络模型，逼近主控环境变量与位移偏离项之间的非线性关系。根据蠕变阶段和变形对环境变量响应情况，实时调整模型，建立起滑坡变形预测的动态灰色-进化神经网络（GM-ENN）模型。将此预测思路和方法应用于三峡库区某滑坡变形预测研究中，证实了模型的有效性和实用性，显示了动态预测的重要性。

Abstract

Landslide deformation prediction has significant practical value that can give the guide for preventing the disaster and protecting the people’s life and property safety. Form the point of system theory

the displacement time-series can be divided into trend item and deviate item. Combined with rheological theory of rock and soil and principle of time-series

these two items can be researched based on deep research of main environmental variables that have obvious influences on landslide deformation. The trend item of displacement time-series can be extracted by grey system model. Evolutionary neural network

constructed by combining genetic algorithm and artificial neural network

can be used to construct the nonlinear relationship between main environmental variables and deviate item. According to creep stage and deformation response to the environmental variables

the comprehensive model must be changed in real time. So the dynamic gray model-evolutionary neural network prediction model of landslide deformation can be constructed by this train of thought. Applying this thinking and method into research of some landslides in the Three Gorges reservoir area

the validity and practical value of this model can be demonstrated. And it also shows that the dynamic prediction of landslide deformation is very crucial.

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Related Institution

Department of Civil Engineering, Wuhan Polytechnic University

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