A Slope Instability Prediction Method Based On Improved Fuzzy Clustering Iteration And Neural Network

Landslide prediction and forecast can effectively reduce the loss caused by the landslide,and it has been widely used in the prevention and control of the landslide.At present,the research on the prediction method of the slope st ability is in constant development and improvement.In this paper,based on th e theory of fuzzy clustering iterative theory,a new method of landslide predict ion and forecast is proposed.The main research contents include the following aspects:(1)In order to improve the prediction accuracy,the data collection and preprocessing scheme of the slope is designed.The 3D data collection scheme is designed,and the theory of wavelet denoising is introduced.Secondly,the original fuzzy clustering iterative model is used to determine the weights of the factors which affect the stability of the slope,and the gray correlation analysis theory is used to avoid the subjectivity of determining the weight of each factor.(2)Based on the improved fuzzy clustering iterative model,a method for evaluating the stability of the slope is constructed by the method of influencing the stability of the slope,and the BP neural network(BP-ANN)-(Bezdek-ISODATA)composite model is proposed to predict the future state of the slope.(3)For the prediction of the slope instability,in order to facilitate the analysis and calculation,the program design is based on Matlab.(4)The proposed method is applied to the same engineering example.The engineering practicability of the method is confirmed by comparing the two schemes.