基于厄米特插值和时间序列模型在沉降监测中的应用

针对沉降监测中用时间序列分析数据样本较少、处理精度不高的问题,本文引入厄米特插值,提出用厄米特插值法对数据进行插值,增加数据样本,然后用时间序列对数据进行建模分析。为了验证用厄米特插值后的数据建模精度,将上述理论运用到工程实例中,用时间序列分析分别对厄米特插值处理后的数据和原始数据进行建模分析,得到用厄米特插值处理后的数据进行时间序列分析建模的平均绝对误差比原始数据建模的平均绝对误差高0.083 8 mm。说明厄米特插值和时间序列组合模型精度比较高。

Based on the Hermitian Interpolation and Time Series Model in the Subsidence Monitoring Research

In order to solve the problem that the data samples in the settlement monitoring are less accurate by time series analysis, the Hermite interpolation is introduced, and the data is interpolated by the Hermite interpolation to increase the data samples, and then use the time series to model the data analysis. In order to verify the accuracy of the data modeling with Hermite interpolation, the a-bove theory is applied to the engineering example. The time series analysis is used to model the data and the original data of the HEr-mit interpolation process respectively. Time-series analysis of the data after special interpolation processing The average absolute error of the modeling is 0.0838 mm higher than the average absolute error of the original data modeling. Indicating that the Hermite interpo-lation and the time series combination model are relatively accurate.