Predicting Natural and Chaotic Time Series with a Swarm-Optimized Neural Network
Juan A. Lazzús · Chinese Physics Letters · 2011
Natural and chaotic time series are predicted using an artificial neural network (ANN) based on particle swarm optimization (PSO). Firstly, the hybrid ANN+PSO algorithm is applied on Mackey—Glass series in the short-term prediction x ( t + 6), using the current value x ( t ) and the past values: x ( t − 6), x ( t − 12), x ( t − 18). Then, this method is applied on solar radiation data using the values of the past years: x ( t − 1), ..., x ( t − 4). The results show that the ANN+PSO method is a very powerful tool for making predictions of natural and chaotic time series.