Deformation Characteristics Of A Highway Slope And Stability Analysis Based On Chaotic Neural Network

As China’s urbanization is speeding up,the city scale is expanding constantly,especially in mountainous city,large and small mountains will inevitably exist around infrastructures,and this also increases various forms of slopes.In order to prevent all kinds of geological disasters caused by the slope,it is necessary to mastery the stability of the slope in real-time.This paper focuses on the deformation characteristics and stability of a high steep rock slope,which has important practical significance and engineering value to ensure the safety of slope and the safety of people’s lives and property.On the basis of reading a large number of relevant literatures at home and abroad,this paper analyzes the deformation characteristics and stability combined with an example of rock slope.The main contents of the research are as follows:(1)According to the site condition of a rock high steep slope,the monitoring scheme was formulated,and the deformation characteristics of the slope were analyzed combined with the field monitoring results.The results show that the vertical displacement of the slope is mainly affected by the progress of construction and the type of rock mass,and shows a certain “hysteresis quality”;The horizontal displacement of the slope is mainly concentrated in the construction stage.When the construction is over,the supporting structure system begins to play a role,and limits the horizontal displacement of the rock mass;The force of the anchor bars shows tension or compression,which is mainly related to the different deformation of internal rock mass and external rock mass.(2)Midas GTS software is used to simulate the slope.The rationality of the model is obtained by comparing the simulation results with the measured data,so as to calculate the stability coefficient of each unit slope.(3)According to the nonlinear characteristics of slope deformation,it is considered that the slope rock mass system belongs to the open system and it is in non-equilibrium state,and the nonlinear interaction exists within the system which has fluctuation.The deformed rock mass can form dissipative structure.The Kolmogorov entropy,which reflects the degree of chaos,is quantitatively calculated.It is proved that the entropy change exists in the process of slope deformation.When the entropy is reduced to a certain value,the rock mass system will lose its stability.The entropy that reflects the degree of rock mass chaos is calculated by phase space reconstruction,which proves that it is necessary to consider the nonlinear characteristics of rock mass when slope stability is calculated.(4)This paper analyzes the practicability of the commonly used chaotic neural network model,and evaluates the stability of the rock slope by predicting the safety factor of the rock slope;The Kolmogorov entropy obtained from information entropy is added to the input layer of the chaotic neural network,and the original chaotic neural network model is improved.The improved model is introduced into the slope stability evaluation system and applied to the engineering practice.Compared with the stability coefficient obtained by numerical simulation,it is found that the prediction result of the improved chaotic neural network is consistent with reality,and it can be applied to slope stability analysis.