Nonlinear coupled model for predicting slope displacement and its application

GE Hai-yu; TU Jin-song

English Version Journal Login

您当前的位置：

首页 >

文章列表页 >

Nonlinear coupled model for predicting slope displacement and its application

更新时间：2026-06-25

- Nonlinear coupled model for predicting slope displacement and its application
- Vol. 32, Issue 6, (2011)
- 作者机构：
  
  皖西学院建筑与土木工程学院,安徽,六安,237012
- 作者简介：
- 基金信息：
- DOI：
  CLC： TU472
- Online First：21 June 2011，
  
  Published：2011
- 稿件说明：
移动端阅览
GE Hai-yu, TU Jin-song. Nonlinear coupled model for predicting slope displacement and its application[J]. 2011, 32(6).
DOI：

GE Hai-yu, TU Jin-song. Nonlinear coupled model for predicting slope displacement and its application[J]. 2011, 32(6). DOI：

摘要

通过边坡现场监测位移序列来预测未来时间边坡的位移，可以有效地评价和判断边坡的稳定性。多种非线性分析方法的组合可以有效提高预测精度，将灰色理论与投影寻踪回归各自的优缺点的基础上，提出了将二者相结合的一种新的预测模型——时序投影寻踪回归模型。新模型既发挥了灰色预测方法中“累加生成”的优点，弱化了原始序列中随机扰动因素的影响，增强了数据的规律性，又充分利用了投影寻踪回归方法易于描述非线性关系的优良特性，避免了灰色预测方法及模型存在的理论缺陷。同时，对模型的可靠性进行了验证。将文中提出的时序投影寻踪回归方法应用到 2 个工程实例，研究结果表明该模型预测值与实测值吻合较好，具有较高的精度，可为边坡位移的预测提供一条新的途径。

Abstract

Based on the displacement sequence of slope

the stability of slope could be judged effectively by forecasting the displacement of slope in the future. After analyzing the advantages and disadvantages of grey forecasting methods and projection pursuit regression (PPR) method respectively; a new nonlinear forecasting model of grey projection pursuit regression (GPPR) is proposed. The new model not only developing the advantages of accumulation generation of the grey forecasting method

weakening the effect of stochastic-disturbing factors in original sequence and strengthening the regularity of data

but also using the quickly solving speed and the excellent characteristics of projection pursuit regression method for nonlinear relationship and avoiding the theoretical defects existing in the grey forecasting model. At the same time

the model is verified. At last

two engineering examples are given to testify the effectiveness of the grey projection pursuit regression forecasting method to predict displacements of two slopes. The results show that the new model has higher calculation precision

so as to provide a new way to predict displacements of slopes

关键词

Keywords

references

Views

1843

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Forecasting slope displacements based on grey least square support vector machines

Fractional nonlinear creep constitutive model of salt rock

Development of software for nonlinear analysis of single pile response based on load transfer method and its application

A nonlinear constitutive model for municipal solid waste considering effects of degradation

Application of mixing method to calculation of row pile anchor support in deep excavation

Related Author

MA Wen-tao

WU Fei

LIU Jian-feng

WU Zhi-de

BIAN Yu

ZHOU Zhi-wei

LIN Peng

LI Shu-cai

Related Institution

College of Mathematics & Computer Engineering, Ningxia University

Langfang Branch, China Research Institute of Petroleum Exploration and Development

Key Laboratory of Energy Engineering Safety and Disaster Mechanics of Ministry of Education, Sichuan University

College of water Resources and Hydropower, Sichuan University

State Key Laboratory for Geomechanics and Deep Underground Engineering, China University of Mining & Technology

AI问答

⁰