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Prediction of Seawall Settlement Based on a Combined LS-ARIMA Model

机译：基于组合LS-ARIMA模型的海堤沉降预测

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摘要

The analysis and prediction of seawall settlement are important for seawall engineering maintenance and disaster prevention. Based on the measured seawall settlement time series data, a combined LS-ARIMA forecasting model that fits the trend item by the least-square (LS) method and the season item by the differential self-regression moving average (ARIMA) model was proposed in this study. The monitoring data of one seawall project in Zhejiang, China, is taken as an example to verify the model efficiency and prediction ability. The results show that the prediction accuracy of the new combined LS-ARIMA model was high, with the average relative error (ARE) of 0.23%, much better than that of the traditional ARIMA model (ARE = 0.70%) and the GM (1, 1) model (ARE = 33.43%). This new model has clear physical conception and can effectively improve the prediction accuracy, implying that it can fully tap the dynamic information of monitoring data. The proposed model in this study provides a new research idea for data analysis and prediction of the seawall settlement.
机译：海堤沉降的分析和预测对于海堤工程的维护和防灾具有重要意义。基于测得的海堤沉降时间序列数据，提出了一种组合的LS-ARIMA预测模型，该模型通过最小二乘（LS）方法拟合趋势项，并通过差分自回归移动平均（ARIMA）模型拟合季节项。这项研究。以浙江某海堤工程的监测数据为例，验证了模型的有效性和预测能力。结果表明，新的组合LS-ARIMA模型的预测精度很高，平均相对误差（ARE）为0.23％，远优于传统ARIMA模型（ARE = 0.70％）和GM（1 ，1）模型（ARE = 33.43％）。该新模型具有清晰的物理概念，可以有效地提高预测精度，这意味着它可以充分利用监测数据的动态信息。本研究提出的模型为海堤沉降的数据分析和预测提供了新的研究思路。

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  • 来源
    《Mathematical Problems in Engineering》 |2017年第6期|7840569.1-7840569.7|共7页
  • 作者

    Qin Peng; Cheng Chunmei;

  • 作者单位

    Zhejiang Univ Water Resources & Elect Power, Inst Hydraul & Environm Engn, Hangzhou 310018, Zhejiang, Peoples R China;

    Zhejiang Univ Water Resources & Elect Power, Inst Geomat & Municipal Engn, Hangzhou 310018, Zhejiang, Peoples R China;

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