Application of Partial Least-squares Regression to Seepage Monitoring Model

摘要：

Among the indicators of seepage monitoring model, there is serous collinearitiy between each water level, water levels and rainfalls. In a seepage monitoring model built by ordinary multiple linear regression, the multicollinearity between each monitoring indicator will influence the parameter estimation, enlarge the model error and damage the robustness of model. To avoid multicollinearity’s disturbance, partial least-squares regression which can identify system information and noise is introduced to model, and a program is compiled. It is illustrated by a case that PLSR can solve the multicollinerity problem of monitoring indicators and give reasonable goodness-of-fit.

关键词： partial least-squares regression seepage monitoring model prototype observation

作者: LI Zong-kun CHEN Le-yi

作者单位: School of Environment&Water Conservancy, Zhengzhou University, Zhenzhou, 450002, China

会议类型: 国际会议

会议名称: 2005年大坝安全与堤坝隐患探测国际学术研讨会(International Symposium on Dam Safety and Detection of Hidden Troubles of Dams and Dikes)

会议地点: 西安

会议语种:英文

页码: 1-9

在线出版日期: 2005-11-01（万方平台首次上网日期，不代表论文的发表时间）