Combined Forecasting Model of Subgrade Settlement Based on Least Square Twin Support Vector Regession
GAO Hui, Song Qi-chao, Huang Jun · International Journal of Hybrid Information Technology · 2016
Due to the normal forecasting methods for subgrade settlement using observation data have different applicabilities, and the predicting results has bigger volatility and lower accuracy. The Combined forecasting model of subgrade settlement based on Least Square twin support vector regession is put forward in this paper. At the first, according to the basic settlement law of subgrade and characteristics of settlement curve, the growth curve with the S-type characteristics are choosed as single forcasting model; Then taking prediction results of each individual model as the least square support vector regression model input and to construct the combined forecasting model of subgrade settlement. The result of engineering practice shows that the proposed method has better prediction accuracy and stability.