Abstract Geodesy data usually contains many uncertainties with unknown statistical information, possibly causing morbid theory model and affecting the accuracy and reliability of parameter estimation. This paper researches the mechanical principle of the nonlinear time series evolution system of slope displacements, and improves the original model by using polynomial fitting. In the process of parameters calculation, the negative influences of results caused by uncertainties of measurement data are considered. The accuracy ofparameters calculation is improved by restricting uncertainty and using the min-max criterion. Comparing the forecasting results with displacement observational data shows that the results of the least-squares with uncertainty (ULS) approach are closer to measurement data, as compared with least-square (LS) and total least-square(TLS). It is also indicated that the effectiveness of predicting displacements by improved nonlinear time series evolution system of slope displacements.
XIAO Zhaobing,SONG Yingchun,XIE Xuemei. Uncertainty Analysis on Improved Nonlinear Time Series Evolution System of Slope Displacements[J]. jgg, 2018, 38(2): 136-140.
XIAO Zhaobing,SONG Yingchun,XIE Xuemei. Uncertainty Analysis on Improved Nonlinear Time Series Evolution System of Slope Displacements[J]. jgg, 2018, 38(2): 136-140.