Prediction of Siltation from a Rainfall in Check Dam Based on RBF Neural Network

Abstract

Due to the complex nonlinear characteristics between erosive rainfall and corresponding sediment volume, radial basis function (RBF) neural network is adopted to predict siltation in matlab2010 environment, and the results were compared with that one from BP neural network. In the course, the 3 major indicators of a rainfall such as single rainfall erosivity (R), maximum rainfall intensity in thirty minutes (I30) , rainfall quantity(P) are as input vectors, with the actual sediment deposition as a target vector. The results show that: RBF neural network is better than BP neural network in forecasting accuracy, computation speed, fitting accuracy.