Exponential smoothing method based on wavelet transform for slope displacement prediction

Wei Hu, Xing-guo Yang, Fugang Xu, Ming-hui Hao
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引用次数: 1

Abstract

It has important significance in engineering to analyze rock slope's evolution rule and forecast its development trend based on the safety monitoring displacement data. The actual slope monitoring sequence is non-stationary time series containing a number of errors, therefore, firstly discrete stationary wavelet transform (DSWT) are used to denoising for monitoring data, then the reconstruction series are transformed into a stationary sequence by first-order difference, finally exponential smoothing method is used to prediction for the stationary differential sequence. The combination forecasting model is applied to high slope displacement prediction on the left bank of Jinping I Hydropower Station, the calculation results show that the combined model have higher forecast accuracy compared with other prediction methods, most of the relative errors of the prediction results are less than 5%, meeting engineering prediction requirements.
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基于小波变换的指数平滑法边坡位移预测
基于安全监测位移数据分析岩质边坡的演化规律并预测其发展趋势具有重要的工程意义。实际的边坡监测序列是非平稳的时间序列,存在一定的误差,因此首先采用离散平稳小波变换(DSWT)对监测数据进行去噪,然后将重建序列通过一阶差分变换为平稳序列,最后采用指数平滑法对平稳微分序列进行预测。
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