Mine Slope Deformation Prediction Model Based On Gene Expression Programming

Mine slope deformation is the universal phenomenon of mine, if the deformation of slope beyond the limit, it will pose significant dangers, and even form landslides and other disastrous consequences. Master of slope deformation trend, take corresponding measures in advance can effectively reduce the disaster occurrence probability and the loss caused by the disaster. At present, the existing prediction methods have certain limitations, so use the new method to predict the mine slope deformation effectively has important significance.This paper firstly introduces the domestic and foreign research present situation of mine slope deformation forecast and gene expression programming; Secondly, illustrates the principle of slope deformation monitoring and several prediction model of mine slope; And then use the wavelet threshold denoising method, and developed a wavelet threshold denoising procedures to pretreat the mine slope monitoring data which contain noise; In addition, based on gene expression programming principle and arithmetic process, using C# program language to design the program of mine slope deformation prediction in the Visual Studio programming environment; And use the mine slope monitoring data of Dexing city as the training data to predict the deformation of this mine slope, at the same time, using BP neural network forecasting model and GM(1,1) gray prediction model to predicted the deformation of a mine slope in Dexing city.The results show that, the error of predicted value obtained by GEP model is 1 to 5 mm, the error of predicted value obtained by BP neural network prediction model is 4 to 10 mm, and the error of predicted value obtained by GM(1,1) forecasting model is 8-13 mm. Prove that the effect of mine slope prediction model based on gene expression programming is better, and it’s more suitable to forecast the mine slope deformation in Dexing city, thus to find an effective method for prediction of mine slope deformation.