Chaotic time series prediction by artificial neural networks
Marjan Kuchaki Rafsanjani, Meysam Samareh · Journal of Computational Methods in Sciences and Engineering · 2016
In this paper, we used four types of artificial neural network (ANN) to predict the behavior of chaotic time series. Each neural network that used in this paper acts as global model to predict the future behavior of time series. Prediction process is based on embedding theorem and time delay determ ined by this theorem. This ANN applied to the time series that generated by Mackey-glass equation that has a chaotic behavior. At the end, all neural networks are used to solve this problem and their results are compared and analyzed.