Notice of RetractionEvaluation on the Stability of Rock Mass Deformation Based on Chaotic Muation -RPNN Model
To analysis the stability of rock mass long-term developing deformation,the chaotic muation -RPNN model is built. Combining the chaos theory,the muation theory is introduced, and the stability of rock mass deformation is evaluated by chaotic muation -RPNN model. The lost measured displacement data are interpolated by using the higher order polynomial methos, and the long-term displacement is forecasted,and the stability of rock mass long-term developing deformation is analyzed. Research shows that the strend of predicted displacement is approximately the same as that of measuring displacement,and there is no suddenly dropped or sudden increased phenomena,and the displacement increasing strend of some measuring point remains stable with Lower growth trend, and the deformation of rock mass is strending to be stable.
Analysis on characteristic parameters of deformation of rock around underground powerhouse based on chaos theory
In order to explore the rules of deformation of rock around underground powerhouse, the chaos theory is introduced and the chaos characteristic parameters are studied systematically and fully.Correlation dimension D is determined by improved G-P method,and maximum lyapunov exponent λ_1 is calculated by using the values of embedding dimension m and delay time τ computer from synthetic analyzing G-P method,C-C method and multiple autocorrelation method.Combining multi-points measuring displacement data of rock around Xiaowan underground powerhouse,the results show that multi-points measuring displacement data at crown apex and those at the measuring-point in 30m depth of arch aboutment do not have the chaos dynamic feature,but the others of arch abutment and those in wall have chaos feature,thus D0,m and τ are optimized,λ_10.So the study provides a new thought for the deformation rules of rock around underground powerhouse.
APPLICATION OF GREY-NEURAL NETWORK MODEL TO LANDSLIDE DEFORMATION PREDICTION
According to the monotonously increasing characteristics and the nonlinear characteristics of landslide displacement time series,the displacement of landslide is decomposed into trend item and random item based on the responding composition model.The trend and random items of displacement time series are predicted by grey-neural network model;and the implementation process of grey-neural network model is discussed.As an example,the grey-neural network model is applied to the prediction of the short-term displacement of Maoping landslide based on the in-situ displacement data.The reasonable result shows the validity and feasibility of the grey-neural network model for landslide displacement prediction.