TIMES SERIES PREDICTION USING ICA ALGORITHMS VS. PARALLEL NEURAL NETWORKS

摘要

In this paper we propose a new method for volatile time series forecasting using Independent Component Analysis (ICA) algorithms and filtering as preprocessing tools. The preprocessed data will be introduce in a based radial basis functions (RBF) Artificial Neural Network (ANN) and the prediction result will be compared with the one we get without these preprocessing tools or with the high computational cost based on parallel neural networks (PNN).