%0 Journal Article
%A YANG Zhen-xing
%A CHEN Fei-fei
%A MA Huan-yuan
%A LI Zhong-yan
%T Combinatorial  Forecasting of Slope Deformation Based onRegression Analysis and Wavelet Transform
%D 2017
%R 10.11988/ckyyb.20160101
%J Journal of Changjiang River Scientific Research Institute
%P 38-42
%V 34
%N 4
%X In order to effectively estimate the  variation trend of slope deformation, we employed  regression analysis and wavelet transform to decompose the  trend term and error term of slope deformation. In subsequence we selected  data of optimal decomposition and predicted series of trend term and error term by using BP and RBF neural network. Then, we obtained the  forecast results of single term and analyzed the  forecast results  of fixed weight combination  and non-fixed weight combination. Results showed that the results of decomposing trend term and error term   by different    methods are  different.Among the methods, polynomial regression with power of six. Fourier regression with power of five  and seven  and wavelet transform of sym2 have better results. Moreover,  partial prediction is prior to conventional prediction of single term, which verifies the effectiveness of partial prediction in the present research. According to combinatorial forecasting results,  fixed weight and non-fixed weight   both    obviously improved prediction accuracy, and the prediction accuracy of the latter is better than that of the former.
%U http://ckyyb.crsri.cn/EN/10.11988/ckyyb.20160101