Author(s)

Kai Yan¹, Jiaye Wu^2*, Yingqian Zhang², Lu Yang³, Yixiong Zhang², Haiyang Yuan⁴, Ying Huang⁴

¹School of Management of Sichuan University of Science & Engineering, Zigong, China.
²Sichuan Shengtuo Testing Technology Co. LTD., Zigong, China.
³School of Civil Engineering of Northeast Forestry University, Harbin, China.
⁴School of Civil Engineering of Chengdu University of Technology, Chengdu, China.

The prediction of deep horizontal displacement of slope soil is an important part of slope deformation monitoring, which has important guiding significance for the prevention of slope safety accidents. Holt-Winters model is suitable to predict the data series of deep horizontal displacement of slope soil, which show both trend growth and seasonal fluctuation. Firstly, this paper selected the data set as the original data for empirical analysis which is deep horizontal displacement of soil after pretreatment from the specific slope monitoring project, then used the Holt-winters’ damped model to perform data mining, finally, compared with the traditional prediction methods including the neural-network model and the k-nearest neighbor classification. The results show that the damped Holt-winters model has the highest prediction accuracy.

Safety Engineering, Deep Horizontal Displacement of Slope Soil, Damped Holt-Winters Model, Forecasting

Yan, K. , Wu, J. , Zhang, Y. , Yang, L. , Zhang, Y. , Yuan, H. and Huang, Y. (2019) Prediction Method of Deep Horizontal Displacement of Slope Soil Based on Damped Holt-Winters Model. Journal of Service Science and Management, 12, 391-406. doi: 10.4236/jssm.2019.123027.