A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Landslide displacement prediction method based on wavelet transform-rough set-support vector regression (WT-RS-SVR) combination
The invention provides a landslide displacement prediction method based on wavelet transform-rough set-support vector regression (WT-RS-SVR) combination. By means of the method, according to the characteristics of the influence factors of landslide displacement, the complex displacement process and landslide displacement monitor data measured in real time, accumulative displacement of a typical monitor point is decomposed into trend-term displacement and periodic-term displacement through WT, and a trend-term displacement prediction function is obtained through curve fitting; screening is conducted on the influence factors of the landslide displacement through an RS algorithm, and selected factor sets are used as input factor sets of an SVR machine, accordingly a landslide displacement optimization prediction model based on WT-RS-SVR combination is established, and the precision of a prediction result is analyzed and evaluated. The prediction result of the landslide displacement prediction method can well embody the development and change tendency of the landslide displacement. The landslide displacement prediction method has high prediction capacity, and is accurate, effective and practical.
Landslide displacement prediction method based on wavelet transform-rough set-support vector regression (WT-RS-SVR) combination
The invention provides a landslide displacement prediction method based on wavelet transform-rough set-support vector regression (WT-RS-SVR) combination. By means of the method, according to the characteristics of the influence factors of landslide displacement, the complex displacement process and landslide displacement monitor data measured in real time, accumulative displacement of a typical monitor point is decomposed into trend-term displacement and periodic-term displacement through WT, and a trend-term displacement prediction function is obtained through curve fitting; screening is conducted on the influence factors of the landslide displacement through an RS algorithm, and selected factor sets are used as input factor sets of an SVR machine, accordingly a landslide displacement optimization prediction model based on WT-RS-SVR combination is established, and the precision of a prediction result is analyzed and evaluated. The prediction result of the landslide displacement prediction method can well embody the development and change tendency of the landslide displacement. The landslide displacement prediction method has high prediction capacity, and is accurate, effective and practical.
Landslide displacement prediction method based on wavelet transform-rough set-support vector regression (WT-RS-SVR) combination
HU YOUJIAN (author) / ZHANG KAIXIANG (author) / NIU RUIQING (author)
2016-01-13
Patent
Electronic Resource
English
IPC:
E02D
FOUNDATIONS
,
Gründungen
Regression models for estimating coseismic landslide displacement
| Elsevier | 2007
Regression models for estimating coseismic landslide displacement
| Online Contents | 2007
Regression models for estimating coseismic landslide displacement
| British Library Online Contents | 2007