基于改进灰色–时序分析时变模型的边坡位移预测

doi:10.13722/j.cnki.jrme.2014.s2.049

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摘要边坡位移的产生及其演变规律，对评价边坡的稳定性极为重要。基于模糊不确定性和随机不确定性以及变形参数所表现出的某种规律，将灰色理论和传统的时间序列分析法相结合，并用二次平滑法对灰色模型进行修正，利用改进GM(1，1)提取边坡位移的趋势项，使非平稳时序转化为平稳时序以进行ARMA或AR时序分析。并根据检测数据的更新，采取实时跟踪算法，进行等维信息变换，建立改进灰色–时序分析时变预测模型。并将该预测模型用于黄金坪水电站进水口边坡工程和长河坝水电站左坝肩边坡工程。对模型检验表明：新模型的预测结果与已有的监测数据相比相对误差基本在5%以下，具有较高的精度，对了解边坡位移的发展趋势以及研究边坡的动态稳定性具有重要意义。

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	张正虎1
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关键词 ：边坡工程；位移；二次平滑法；预测；改进灰色&ndash, 时序分析

Abstract：Cause and evolution law of the displacement of slope are very important for the evaluation of the stability of slope. Based on fuzzy uncertainty and random uncertainty and a certain regularity of deformation parameters，improved grey-time series time-varying prediction model，in which grey theory and traditional time series analysis method are combined，is established on gray model by double smoothing correction. Improved GM(1，1) is utilized to extract the trend term of the displacement of slope. After the extraction，the displacement time series becomes a stable series，which could be processed by ARMA or AR model. According to the detect data update，the model parameters are continuously modified of equal intervals in accordance with real-time tracing algorithm. As a test，the prediction model is used in inlet slope engineering of Huangjinping hydropower station and left abutment slope engineering of Changheba hydropower station. The model test show that relative error between predicted and measured value is mainly less than 5%. The model is of high precision and is of great significance to understand the development trend of the displacement of slope and study the dynamic stability of slope.

Key words： slope engineering displacement double smoothing correction prediction improved grey-time series analysis

引用本文:

张正虎1，2，袁孟科1，2，邓建辉1，2，薛守宁3. 基于改进灰色–时序分析时变模型的边坡位移预测[J]. 岩石力学与工程学报, 2014, 33(S2): 3791-3797.
ZHANG Zhenghu1，2，YUAN Mengke1，2，DENG Jianhui1，2，XUE Shouning3. DISPLACEMENT PREDICTION OF SLOPE BASED ON IMPROVED GREY-TIME SERIES TIME-VARYING MODEL. , 2014, 33(S2): 3791-3797.

链接本文:

https://rockmech.whrsm.ac.cn/CN/10.13722/j.cnki.jrme.2014.s2.049 或 https://rockmech.whrsm.ac.cn/CN/Y2014/V33/IS2/3791

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