大型边坡多测点组合变形预测方法及工程应用

谈小龙

长江科学院院报 ›› 2014, Vol. 31 ›› Issue (11) : 143-148.

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长江科学院院报 ›› 2014, Vol. 31 ›› Issue (11) : 143-148. DOI: 10.3969/j.issn.1001-5485.2014.11.0282014,31(11):143-148
工程设计与施工监控

大型边坡多测点组合变形预测方法及工程应用

  • 谈小龙a,b
作者信息 +

Combinatorial Method of Deformation Prediction Based on Multipoint Monitoring for Large Slope and Its Engineering Application

  • TAN Xiao-long1,2
Author information +
文章历史 +

摘要

单测点时序分析模型是单一的独立模型,没有充分考虑同类监测点空间变形上的相关性,往往不能反映边坡的整体变形趋势和规律。在单测点灰色预测模型基础上,将聚类分析方法应用于边坡监测数据的时间序列关系分析,并考虑多测点的空间关联性,建立多测点整体变形预测模型。结合锦屏一级水电站边坡工程进行应用研究。结果表明,多测点整体变形预测方法的可靠性与准确性明显高于单测点预测模型。

Abstract

Time series analysis model based on single monitoring point is independent which doesn’t fully consider the space correlation of similar monitoring points, and couldn’t reflect the overall trend and pattern of slope deformation. On the basis of single point grey forecasting model, we applied fuzzy clustering method to the time series relationship analysis of slope monitoring points and established a deformation prediction model in consideration of multipoint space relevance. The model is applied to slope engineering of Jinping hydropower station and the results show that the reliability and accuracy of this method are obviously higher than those of single point prediction model.

关键词

边坡 / 时间序列 / 模糊聚类 / 多测点 / 组合预测模型

Key words

slope / time series / fuzzy clustering / multipoint monitoring / combinatorial prediction model

引用本文

导出引用
谈小龙. 大型边坡多测点组合变形预测方法及工程应用[J]. 长江科学院院报. 2014, 31(11): 143-148 https://doi.org/10.3969/j.issn.1001-5485.2014.11.0282014,31(11):143-148
TAN Xiao-long. Combinatorial Method of Deformation Prediction Based on Multipoint Monitoring for Large Slope and Its Engineering Application[J]. Journal of Changjiang River Scientific Research Institute. 2014, 31(11): 143-148 https://doi.org/10.3969/j.issn.1001-5485.2014.11.0282014,31(11):143-148
中图分类号: TU454   

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基金

国家自然科学基金重点项目(50539110);国家科技支撑计划项目(2008BAB29B01)

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