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文章基本信息

  • 标题:Combined Forecasting Model of Subgrade Settlement Based on Least Square Twin Support Vector Regession
  • 本地全文:下载
  • 作者:GAO Hui ; Song Qi-chao ; Huang Jun
  • 期刊名称:International Journal of Hybrid Information Technology
  • 印刷版ISSN:1738-9968
  • 出版年度:2016
  • 卷号:9
  • 期号:6
  • 页码:135-142
  • DOI:10.14257/ijhit.2016.9.6.12
  • 出版社:SERSC
  • 摘要: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.
  • 关键词:Subgrade Settlement prediction; Combination forecast model; Least Square ; twin support regession
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