Filtering and Multi-Scale RBF Prediction Model of Rainfall Based on EMD Method
Xinxia Liu, Anbing Zhang, Cuimei Shi, Haifeng Wang · 2009
Rainfall prediction is a key question in the study field of hydrology and water resources. Point to non-linear, chaotic character and with the noise characteristics Run-off signals, we propose a new model based on empirical mode decomposition (EMD) and the RBF neural network (RBF). First, rainfall time series will be broken down into a series of different scales intrinsic mode function imf by EMD, Second, the denoise and phase-space reconstruction will be done. The third, we predict each component by RBF. Finally, we reconstruct the final prediction value by each component. Simulation results show that the method have a high accuracy in denoising and prediction of the rainfall sequence.