Application of Support Vector Machine Model on Deformation Forecasting of Deep Foundation Pit in Soft Soil Area

摘要：

Based on the measured time series, deformation regularity of deep foundation pit in soft soil area was predicted using Support Vector Machine (SVM) model Meanwhile, Gauss kernel function and Sequential minimal optimization (SMO) arithmetic were determined, and the results are shown to be in good agreement with measured data and laws reported in paper. At the same time, this study illustrates th at S VM could perform well in solving fuzzy geotechnical engineering problem similar to deformation prediction. As anoth er act, the method and conclusion can be considered as reference for colleagues.

关键词： Deep Foundation Pit in soft soil area Deformation Forecasting Time Series Support Vector Machine Model

作者: Yun-hui. Zhu Chang-feng Ruan Fu-xue Sun

作者单位: Oujiang College, Wenzhou University, 325035, China College of Architecture and Civil Engineering, Wenzhou University, 325035, China

会议类型: 国际会议

会议名称: 2010 International Conference on Circuit and Signal Processing(2010年电路与信号处理国际会议 ICCSP 2010)

会议地点: 上海

会议语种:英文

页码: 50-52

在线出版日期: 2010-12-25（万方平台首次上网日期，不代表论文的发表时间）