English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Tools annual

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Presents the access of premium content as premium feature

Premium Content

Global: Zendy Plus annual

Global: Zendy Free Plan

According to the slope in geotechnical engineering, many displacement monitoring points are usually set to obtain the displacement data to ensure slope stability, these data are typical nonlinear time series, and it has high value about how to make use of displacement monitoring data to do the next step forecast analysis. Due to a certain degree of error, smoothing filter method is used to pretreat the displacement data, eliminate the influence of the error on the results and ensure the rationality. Based on smoothing filter data, these two methods are proposed to predict the displacement of the slope: exponential smoothing and chaos neural network. Both methods are used to make predictive analysis of the displacement monitoring data of outer monitoring point TP/BM27 in high slope of Three Gorges Ship-Lock, forecasting results show that: predictive values are close to measured values, chaos neural network prediction method is better than exponential smoothing method. At the same time, the displacement data with higher reliability and smoothing filter processing are used to make predictive analysis, the results can be more reasonable, so smoothing filter processing plays an important role in the analysis of displacement prediction.

Nonlinear Time Series Predication of Slope Displacement based on Smoothing Filtered Data