Neural Network Modeling and Slope Displacement Prediction Based on Time Series
Chongqing Zhang · Chinese Journal of Underground Space and Engineering · 2009
Slope system is a very complicated nonlinear system which is influenced by many factors,thus,as an explicit behavior of the inherent mechanics phenomena,the displacement of slope are characterized with the strong nonlinear of randomness and indetermination.Because neural network has the performances of the powerful robustness,learning and associative memory function,and data mining,so it has obvious advantage to predict placement of slope to the data of single time series which existing inner link.Take this as the starting point,the prediction model is established based on time-series and neural network after concluding and analyzing the real observation data.As a test,this model was used in displacement prediction of Yuqian high-way slope.The results of engineering case show that BP neural network is feasible to predict the data of single time series through mining crytic information the average error is 2.27%.After comparing with the method of the traditional gray theory,it is proved this model has the high precision and high fitting degree.