APPLICATION OF WEIGHTED BLOCK RECURSIVE PARTIAL LEAST SQUARES REGRESSION FOR DAM SAFETY MONITORING

摘要：

As a new modeling method, partial least squares regression has been widely used in dam safety monitoring data analysis, but with the accumulation of data, If off-line analysis still is used,calculated rate will be affected, and predicting accuracy will be reduced. In this paper, weighted block recursive partial least squares regression(WBRPLSR) is designed, in this method, weights of sample data are allocated by time sequence, and then by means ofrecursive time blocks, prediction model for dam safety monitoring is established by partial least squares regression. The result of an example shows that efficiency and prediction performance of WBRPLSR model are greatly improved, which has some popularized value.

关键词： dam safety monitoring weighted block recursive partial least squares regression prediction model

作者: Bo Li Chongshi Gu Zhilu Li Lili Liu

作者单位: College of Water Conservancy Hydropower Engineering, Hohai University, Nanjing 210098, China College of Water Conservancy Hydropower, Xian University of Technology, Xian 710048, China

会议类型: 国际会议

会议名称: 第16届亚太地区国际水利学大会暨第3届水工水力学国际研讨会(16th IAHR-APD Congress and 3rd Symoposium of IAHR-ISHS)

会议地点: 南京

会议语种:英文

页码: 1835-1840

在线出版日期: 2008-10-20（万方平台首次上网日期，不代表论文的发表时间）