APPLICATION OF CHAOTIC TIME SERIESLEAST SQUARE SUPPORT VECTOR MACHINE IN DAMS’ SAFETY MONITORING PREDICTION
Zhao Qing 1) ;Li Xiao 1) ;Xu Jinjun 1) ; and Mi Tianyue 2)
1)School of Geodesy and Geomatics, Wuhan University, Wuhan 4300792)Huadong Hydroelectric,Surveying and Mapping Ltd. Corporation of Zhejiang,Hangzhou 310030
Abstract A new model (chaotic time series-least square support) is put forward for solving the problem of medium-long time prediction by use of the dam’s nonlinear deformation data affected by the outer factors. Firstly, the nonlinear deformation data’s phase space is reconstructed based on the phase space reconstruction theory. Then LSSVM (Least Square Support Vector Machine) is used to model and make the mediumlong time prediction from the data in the reconstruction phase space integrated with the outer factors based on the statisticslearning theory. An example testifies the model is effective.
Key words ：
chaotic time series
LSSVM(Least Square Support Vector Machine)
dams’ deformation
safety monitoring
mediumlong time prediction
Received: 01 January 1900
Corresponding Authors:
Zhao Qing
Cite this article:
Zhao Qing ,Li Xiao ,Xu Jinjun et al. APPLICATION OF CHAOTIC TIME SERIESLEAST SQUARE SUPPORT VECTOR MACHINE IN DAMS’ SAFETY MONITORING PREDICTION[J]. , 2008, 28(2): 115-119.
Zhao Qing ,Li Xiao ,Xu Jinjun et al. APPLICATION OF CHAOTIC TIME SERIESLEAST SQUARE SUPPORT VECTOR MACHINE IN DAMS’ SAFETY MONITORING PREDICTION[J]. jgg, 2008, 28(2): 115-119.
URL:
http://www.jgg09.com/EN/ OR http://www.jgg09.com/EN/Y2008/V28/I2/115
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