Application of Partial Least-squares Regression Method to Dam Displacement Monitoring
Dongjie Yue
Abstract
Dongjie Yue
Abstract
Multiple correlations often exist among the different impact factors in a dam displacement prediction model,and will bring about a series of negative effects on regression modeling and analysis.However,the partial least-squares regression method can solve this problem in a reasonable manner.Based on the principle of PLS,and also combined with the measured site data,a partial least-squares regression model and a stepwise regression model for dam displacement monitoring are established.A comparison of these two models is made,and good results are achieved.
OpenAlex reports 1 citations for this work. Citation counts describe recorded attention and do not establish research quality.
A contribution statement is not available in the OpenAlex record.
Method details are not available in the OpenAlex metadata.
Findings are not separately available in the OpenAlex metadata.
Limitations are not available in the OpenAlex metadata.
Application details are not available in the OpenAlex metadata.
Multiple correlations often exist among the different impact factors in a dam displacement prediction model,and will bring about a series of negative effects on regression modeling and analysis.However,the partial least-squares regression method can solve this problem in a reasonable manner.Based on the principle of PLS,and also combined with the measured site data,a partial least-squares regression model and a stepwise regression model for dam displacement monitoring are established.A comparison of these two models is made,and good results are achieved.
Key concepts: Partial least squares regression, Regression analysis, Regression, Displacement (psychology), Stepwise regression, Total least squares, Statistics, Least-squares function approximation