Abstract：Based on the displacement sequence of slope，the stability of slope could be judged effectively by forecasting the displacement of slope in the future. Because the nonlinear evolution of slope could be obtained by learning the sample repeatedly with neural network，the forecast effect of neural network is better than those of traditional methods. Compared with BP neural network，RBF neural network has better capability of approximation and globe optimum characteristics as a well-behaved feedforward network. Based on the time series of the slope displacement，RBF neural network is adopted to construct the forecast models；and the nearest neighbor-clustering algorithm is used to forecast the displacement of slope. The method has the advantages of simple structure，faster learning velocity and better precision of forecast；and the extrapolated capability of RBF neural network is better than that of BP neural network. Finally，two engineering examples are given to testify the effectiveness of the forecast method to displacement of slope based on RBF neural network.
